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  <div class="headertitle"><div class="title">WeightedDataset.h</div></div>
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<a href="_weighted_dataset_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Weighted data sets for (un-)supervised learning.</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * \par</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * This file provides containers for data used by the models, loss</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * functions, and learning algorithms (trainers). The reason for</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * dedicated containers of this type is that data often need to be</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * split into subsets, such as training and test data, or folds in</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * cross-validation. The containers in this file provide memory</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * efficient mechanisms for managing and providing such subsets.</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * The speciality of these containers are that they are weighted.</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * </span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * </span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> *</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * \author    O. Krause</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * \date       2014</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> *</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> *</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * </span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * </span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment"> * </span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="comment"> * </span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="comment"> *</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment"> */</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span> </div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="preprocessor">#ifndef SHARK_DATA_WEIGHTED_DATASET_H</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="preprocessor">#define SHARK_DATA_WEIGHTED_DATASET_H</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span> </div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="preprocessor">#include &lt;<a class="code" href="_dataset_8h.html">shark/Data/Dataset.h</a>&gt;</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span>    <span class="comment"></span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">///\brief Input-Label pair of data</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DataType, <span class="keyword">class</span> WeightType&gt;</div>
<div class="foldopen" id="foldopen00053" data-start="{" data-end="};">
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html">   53</a></span><span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>{</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">   54</a></span>    DataType <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>;</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">   55</a></span>    WeightType <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>;</div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span>    </div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#a44ea6d553a9c404762877e73a27be98a">   57</a></span>    <a class="code hl_function" href="structshark_1_1_weighted_data_pair.html#a44ea6d553a9c404762877e73a27be98a">WeightedDataPair</a>(){}</div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span>    </div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> DataT, <span class="keyword">class</span> WeightT&gt;</div>
<div class="foldopen" id="foldopen00060" data-start="{" data-end="}">
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#a13d962d654eb99ebd5e6efe31b5f870d">   60</a></span>    <a class="code hl_function" href="structshark_1_1_weighted_data_pair.html#a13d962d654eb99ebd5e6efe31b5f870d">WeightedDataPair</a>(</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span>        DataT&amp;&amp; <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>,</div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span>        WeightT&amp;&amp; <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span>    ):<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>),<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>){}</div>
</div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span>    </div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> DataT, <span class="keyword">class</span> WeightT&gt;</div>
<div class="foldopen" id="foldopen00066" data-start="{" data-end="}">
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#ad68bb92f39809cde931acb4a9efd5017">   66</a></span>    <a class="code hl_function" href="structshark_1_1_weighted_data_pair.html#ad68bb92f39809cde931acb4a9efd5017">WeightedDataPair</a>(</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>        <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair&lt;DataT,WeightT&gt;</a> <span class="keyword">const</span>&amp; pair</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>    ):<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>(pair.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>),<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>(pair.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>){}</div>
</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>    </div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> DataT, <span class="keyword">class</span> WeightT&gt;</div>
<div class="foldopen" id="foldopen00071" data-start="{" data-end="}">
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#a827848bbc7d6900c72814dc6260aec1f">   71</a></span>    <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&amp; <a class="code hl_function" href="structshark_1_1_weighted_data_pair.html#a827848bbc7d6900c72814dc6260aec1f">operator=</a>(<a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair&lt;DataT,WeightT&gt;</a> <span class="keyword">const</span>&amp; batch){</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>;</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>;</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>    }</div>
</div>
<div class="foldopen" id="foldopen00076" data-start="{" data-end="}">
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_pair.html#a552caca30cff45615dd102e80694d94a">   76</a></span>    <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&amp; <a class="code hl_function" href="structshark_1_1_weighted_data_pair.html#a552caca30cff45615dd102e80694d94a">operator=</a>(<a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a> <span class="keyword">const</span>&amp; batch){</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#a10989da82db7181438ce1ff19272bd75">data</a>;</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_pair.html#acf28cb8512b93ca53958db8ade244ac9">weight</a>;</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>    }</div>
</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>};</div>
</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span> </div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> D1, <span class="keyword">class</span> W1, <span class="keyword">class</span> D2, <span class="keyword">class</span> W2&gt;</div>
<div class="foldopen" id="foldopen00084" data-start="{" data-end="}">
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"><a class="line" href="namespaceshark.html#a8408e5667c51f973f3a98c237be15dfa">   84</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(<a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair&lt;D1, W1&gt;</a>&amp;&amp; p1, <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair&lt;D2, W2&gt;</a>&amp;&amp; p2){</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>    <span class="keyword">using </span>std::swap;</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(std::forward&lt;D1&gt;(p1.data),std::forward&lt;D2&gt;(p2.data));</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(std::forward&lt;W1&gt;(p1.weight),std::forward&lt;W2&gt;(p2.weight));</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>}</div>
</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span> </div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DataBatchType,<span class="keyword">class</span> WeightBatchType&gt;</div>
<div class="foldopen" id="foldopen00091" data-start="{" data-end="};">
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html">   91</a></span><span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>{</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch_traits.html">BatchTraits&lt;typename std::decay&lt;DataBatchType&gt;::type</a> &gt;::type <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">DataBatchTraits</a>;</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch_traits.html">BatchTraits&lt;typename std::decay&lt;WeightBatchType&gt;::type</a> &gt;::type <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">WeightBatchTraits</a>;</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">   96</a></span>    DataBatchType <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>;</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">   97</a></span>    WeightBatchType <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>;</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span> </div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&lt;</div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        <span class="keyword">typename</span> DataBatchTraits::value_type,</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>        <span class="keyword">typename</span> WeightBatchTraits::value_type</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>    &gt; <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">value_type</a>;</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&lt;</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>        <span class="keyword">decltype</span>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(std::declval&lt;DataBatchType&amp;&gt;(),0)),</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>        <span class="keyword">decltype</span>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(std::declval&lt;WeightBatchType&amp;&gt;(),0))</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#aab93ae72cede17722ce1d1e831e5186d">  106</a></span>    &gt; <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">reference</a>;</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&lt;</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>        <span class="keyword">decltype</span>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(std::declval&lt;<span class="keyword">typename</span> std::add_const&lt;DataBatchType&gt;::type&amp;&gt;(),0)),</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        <span class="keyword">decltype</span>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(std::declval&lt;<span class="keyword">typename</span> std::add_const&lt;WeightBatchType&gt;::type&amp;&gt;(),0))</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#aa6720b317a8ce59206d04aad023c299c">  110</a></span>    &gt; <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">const_reference</a>;</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a9b970bab9307c3425a433d2582a29c58">  111</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">IndexingIterator&lt;WeightedDataBatch&gt;</a> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a9b970bab9307c3425a433d2582a29c58">iterator</a>;</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a0a589f16a9f45a55f7ce78ed8765d4df">  112</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">IndexingIterator&lt;WeightedDataBatch const&gt;</a> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a0a589f16a9f45a55f7ce78ed8765d4df">const_iterator</a>;</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span> </div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> D, <span class="keyword">class</span> W&gt;</div>
<div class="foldopen" id="foldopen00115" data-start="{" data-end="}">
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#ac82c6a85cfc3cedcc5f9ad7ab0d370aa">  115</a></span>    <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#ac82c6a85cfc3cedcc5f9ad7ab0d370aa">WeightedDataBatch</a>(</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>        D&amp;&amp; <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>,</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>        W&amp;&amp; <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a></div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>    ):<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>),<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>){}</div>
</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>    </div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> Pair&gt;</div>
<div class="foldopen" id="foldopen00121" data-start="{" data-end="}">
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#aba773079455339053a533ed884868fc2">  121</a></span>    <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#aba773079455339053a533ed884868fc2">WeightedDataBatch</a>(</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>        std::size_t <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>,Pair <span class="keyword">const</span>&amp; p</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>    ):<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>(<a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">DataBatchTraits</a>::<a class="code hl_function" href="namespaceshark.html#a5478d144c4c997faf5c246dd8e2f85b8" title="creates a batch from a range of inputs">createBatch</a>(p.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>,<a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>)),<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>(<a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">WeightBatchTraits</a>::<a class="code hl_function" href="namespaceshark.html#a5478d144c4c997faf5c246dd8e2f85b8" title="creates a batch from a range of inputs">createBatch</a>(p.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>,<a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>)){}</div>
</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>    </div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> I, <span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00126" data-start="{" data-end="}">
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a9a07bdf59fd11d9f3bd7cf38dedec869">  126</a></span>    <a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>&amp; <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a9a07bdf59fd11d9f3bd7cf38dedec869">operator=</a>(<a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch&lt;I,L&gt;</a> <span class="keyword">const</span>&amp; batch){</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>;</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>        <a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a> = batch.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>;</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>    }</div>
</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span> </div>
<div class="foldopen" id="foldopen00132" data-start="{" data-end="}">
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">  132</a></span>    std::size_t <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>        <span class="keywordflow">return</span> DataBatchTraits::size(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>);</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>    }</div>
</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>    </div>
<div class="foldopen" id="foldopen00136" data-start="{" data-end="}">
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a98dd827f038cb5b040270fe7b04dd0bf">  136</a></span>    <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">iterator</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a98dd827f038cb5b040270fe7b04dd0bf">begin</a>(){</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a9b970bab9307c3425a433d2582a29c58">iterator</a>(*<span class="keyword">this</span>,0);</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>    }</div>
</div>
<div class="foldopen" id="foldopen00139" data-start="{" data-end="}">
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#ad59bbfed85b4dcf79cbc5fec32fb0a7f">  139</a></span>    <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">const_iterator</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#ad59bbfed85b4dcf79cbc5fec32fb0a7f">begin</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a0a589f16a9f45a55f7ce78ed8765d4df">const_iterator</a>(*<span class="keyword">this</span>,0);</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>    }</div>
</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span> </div>
<div class="foldopen" id="foldopen00143" data-start="{" data-end="}">
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a3d52a8bba398c542b279eff348e767ca">  143</a></span>    <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">iterator</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a3d52a8bba398c542b279eff348e767ca">end</a>(){</div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a9b970bab9307c3425a433d2582a29c58">iterator</a>(*<span class="keyword">this</span>,<a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>());</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>    }</div>
</div>
<div class="foldopen" id="foldopen00146" data-start="{" data-end="}">
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#a9d74ee915f51b09f82ea0bd7f0fda253">  146</a></span>    <a class="code hl_class" href="classshark_1_1_indexing_iterator.html">const_iterator</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a9d74ee915f51b09f82ea0bd7f0fda253">end</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#a0a589f16a9f45a55f7ce78ed8765d4df">const_iterator</a>(*<span class="keyword">this</span>,<a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#a54a8f4d8ff69f2d811c7bfc61f70fe1a">size</a>());</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>    }</div>
</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span> </div>
<div class="foldopen" id="foldopen00150" data-start="{" data-end="}">
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#adf2340323a3555f694c2401e9c929078">  150</a></span>    <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">reference</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#adf2340323a3555f694c2401e9c929078">operator[]</a>(std::size_t i){</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#aab93ae72cede17722ce1d1e831e5186d">reference</a>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>,i),<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>,i));</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>    }</div>
</div>
<div class="foldopen" id="foldopen00153" data-start="{" data-end="}">
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno"><a class="line" href="structshark_1_1_weighted_data_batch.html#abe8aa3af931ea176a11c3cd1eb97ad88">  153</a></span>    <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">const_reference</a> <a class="code hl_function" href="structshark_1_1_weighted_data_batch.html#abe8aa3af931ea176a11c3cd1eb97ad88">operator[]</a>(std::size_t i)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>        <span class="keywordflow">return</span> <a class="code hl_typedef" href="structshark_1_1_weighted_data_batch.html#aa6720b317a8ce59206d04aad023c299c">const_reference</a>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>,i),<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>,i));</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>    }</div>
</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>};</div>
</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span> </div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> D1, <span class="keyword">class</span> W1, <span class="keyword">class</span> D2, <span class="keyword">class</span> W2&gt;</div>
<div class="foldopen" id="foldopen00159" data-start="{" data-end="}">
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno"><a class="line" href="namespaceshark.html#a3cc030be2d66d651db977fda36958a8d">  159</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(<a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch&lt;D1, W1&gt;</a>&amp; p1, <a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch&lt;D2, W2&gt;</a>&amp; p2){</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>    <span class="keyword">using </span>std::swap;</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(p1.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>,p2.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#afe97e8d945ac50b033bd2fe8e6c7718f">data</a>);</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(p1.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>,p2.<a class="code hl_variable" href="structshark_1_1_weighted_data_batch.html#a6c2e982d48f580e8f702070e530b9843">weight</a>);</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>}</div>
</div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span> </div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DataType, <span class="keyword">class</span> WeightType&gt;</div>
<div class="foldopen" id="foldopen00166" data-start="{" data-end="};">
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno"><a class="line" href="structshark_1_1_batch_3_01_weighted_data_pair_3_01_data_type_00_01_weight_type_01_4_01_4.html">  166</a></span><span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch</a>&lt;<a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&lt;DataType, WeightType&gt; &gt;</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span>: <span class="keyword">public</span> detail::SimpleBatch&lt;</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>    WeightedDataBatch&lt;typename detail::element_to_batch&lt;DataType&gt;::type, typename detail::element_to_batch&lt;WeightType&gt;::type&gt;</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>&gt;{};</div>
</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span> </div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DataType, <span class="keyword">class</span> WeightType&gt;</div>
<div class="foldopen" id="foldopen00172" data-start="{" data-end="};">
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"><a class="line" href="structshark_1_1_batch_traits_3_01_weighted_data_batch_3_01_data_type_00_01_weight_type_01_4_01_4.html">  172</a></span><span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_batch_traits.html">BatchTraits</a>&lt;<a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>&lt;DataType, WeightType&gt; &gt;{</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno"><a class="line" href="structshark_1_1_batch_traits_3_01_weighted_data_batch_3_01_data_type_00_01_weight_type_01_4_01_4.html#a83a936d6261d5d2fb60c49133a370b92">  173</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> detail::batch_to_element&lt;DataType&gt;::type <a class="code hl_typedef" href="structshark_1_1_batch_traits_3_01_weighted_data_batch_3_01_data_type_00_01_weight_type_01_4_01_4.html#a83a936d6261d5d2fb60c49133a370b92">DataElem</a>;</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno"><a class="line" href="structshark_1_1_batch_traits_3_01_weighted_data_batch_3_01_data_type_00_01_weight_type_01_4_01_4.html#afd0031d901cc3538a3780a5b4769e077">  174</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> detail::batch_to_element&lt;WeightType&gt;::type <a class="code hl_typedef" href="structshark_1_1_batch_traits_3_01_weighted_data_batch_3_01_data_type_00_01_weight_type_01_4_01_4.html#afd0031d901cc3538a3780a5b4769e077">WeightElem</a>;</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;WeightedDataPair&lt;DataElem,WeightElem&gt;</a> &gt; <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">type</a>;</div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>};</div>
</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span> </div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span> </div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span><span class="keyword">namespace </span>detail{</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span><span class="keyword">template</span> &lt;<span class="keyword">class</span> DataContainerT&gt;</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span><span class="keyword">class </span>BaseWeightedDataset : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_i_serializable.html" title="Abstracts serializing functionality.">ISerializable</a></div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>{</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> DataContainerT::element_type DataType;</div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>    <span class="keyword">typedef</span> <span class="keywordtype">double</span> WeightType;</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>    <span class="keyword">typedef</span> DataContainerT DataContainer;</div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;WeightType&gt;</a> WeightContainer;</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> DataContainer::IndexSet IndexSet;</div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span> </div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>    <span class="comment">// TYPEDEFS FOR PAIRS</span></div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_pair.html" title="Input-Label pair of data.">WeightedDataPair</a>&lt;</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>        DataType,</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>        WeightType</div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>    &gt; element_type;</div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span> </div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>&lt;</div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span>        <span class="keyword">typename</span> DataContainer::batch_type,</div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span>        <span class="keyword">typename</span> WeightContainer::batch_type</div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>    &gt; batch_type;</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span> </div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>    <span class="comment">// TYPEDEFS FOR BATCH REFERENCES</span></div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>&lt;</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>        <span class="keyword">typename</span> DataContainer::batch_reference,</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>        <span class="keyword">typename</span> <a class="code hl_typedef" href="group__shark__globals.html#ga79217da1dd034aa18bc553f483e9449c">WeightContainer::batch_reference</a></div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span>    &gt; batch_reference;</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_weighted_data_batch.html">WeightedDataBatch</a>&lt;</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>        <span class="keyword">typename</span> DataContainer::const_batch_reference,</div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>        <span class="keyword">typename</span> <a class="code hl_typedef" href="group__shark__globals.html#gab8037000e57c8d73273e1323ec2efe72">WeightContainer::const_batch_reference</a></div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>    &gt; const_batch_reference;</div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span>    </div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;element_type&gt;::reference</a> element_reference;</div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;element_type&gt;::const_reference</a> const_element_reference;</div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span> </div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span>    <span class="keyword">typedef</span> boost::iterator_range&lt; detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; &gt; &gt; element_range;</div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>    <span class="keyword">typedef</span> boost::iterator_range&lt; detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; <span class="keyword">const</span>&gt; &gt; const_element_range;</div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>    <span class="keyword">typedef</span> detail::BatchRange&lt;BaseWeightedDataset&lt;DataContainer&gt; &gt; batch_range;</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>    <span class="keyword">typedef</span> detail::BatchRange&lt;BaseWeightedDataset&lt;DataContainer&gt; <span class="keyword">const</span>&gt; const_batch_range;</div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span> </div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span><span class="comment"></span> </div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span><span class="comment">    ///\brief Returns the range of elements.</span></div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span><span class="comment">    ///It is compatible to boost::range and STL and can be used whenever an algorithm requires</span></div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span><span class="comment">    ///element access via begin()/end() in which case data.elements() provides the correct interface</span></div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span><span class="comment"></span>    const_element_range elements()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span>        <span class="keywordflow">return</span> const_element_range(</div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span>            detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; <span class="keyword">const</span>&gt;(<span class="keyword">this</span>,0,0,0),</div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>            detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; <span class="keyword">const</span>&gt;(<span class="keyword">this</span>,numberOfBatches(),0,numberOfElements())</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>        );</div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span><span class="comment">    ///\brief Returns therange of elements.</span></div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span><span class="comment">    ///It is compatible to boost::range and STL and can be used whenever an algorithm requires</span></div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span><span class="comment">    ///element access via begin()/end() in which case data.elements() provides the correct interface</span></div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span><span class="comment"></span>    element_range elements(){</div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span>        <span class="keywordflow">return</span> element_range(</div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span>            detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; &gt;(<span class="keyword">this</span>,0,0,0),</div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span>            detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; &gt;(<span class="keyword">this</span>,numberOfBatches(),0,numberOfElements())</div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span>        );</div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span>    }</div>
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno">  240</span>    <span class="comment"></span></div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span><span class="comment">    ///\brief Returns the range of batches.</span></div>
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno">  242</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span><span class="comment">    ///It is compatible to boost::range and STL and can be used whenever an algorithm requires</span></div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span><span class="comment">    ///element access via begin()/end() in which case data.elements() provides the correct interface</span></div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span><span class="comment"></span>    const_batch_range batches()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span>        <span class="keywordflow">return</span> const_batch_range(<span class="keyword">this</span>);</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span><span class="comment">    ///\brief Returns the range of batches.</span></div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span><span class="comment">    ///It is compatible to boost::range and STL and can be used whenever an algorithm requires</span></div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span><span class="comment">    ///element access via begin()/end() in which case data.elements() provides the correct interface</span></div>
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno">  252</span><span class="comment"></span>    batch_range batches(){</div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span>        <span class="keywordflow">return</span> batch_range(<span class="keyword">this</span>);</div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span>    }</div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span><span class="comment"></span> </div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span><span class="comment">    ///\brief Returns the number of batches of the set.</span></div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span><span class="comment"></span>    std::size_t numberOfBatches()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span>        <span class="keywordflow">return</span> m_data.numberOfBatches();</div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno">  260</span><span class="comment">    ///\brief Returns the total number of elements.</span></div>
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno">  261</span><span class="comment"></span>    std::size_t numberOfElements()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>        <span class="keywordflow">return</span> m_data.numberOfElements();</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span>    }</div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span><span class="comment"></span> </div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span><span class="comment">    ///\brief Check whether the set is empty.</span></div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span><span class="comment"></span>    <span class="keywordtype">bool</span> empty()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span>        <span class="keywordflow">return</span> m_data.empty();</div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span>    }</div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span><span class="comment"></span> </div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span><span class="comment">    ///\brief Access to the stored data points as a separate container.</span></div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span><span class="comment"></span>    DataContainer <span class="keyword">const</span>&amp; data()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span>        <span class="keywordflow">return</span> m_data;</div>
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno">  273</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span><span class="comment">    ///\brief Access to the stored data points as a separate container.</span></div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span><span class="comment"></span>    DataContainer&amp; data(){</div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span>        <span class="keywordflow">return</span> m_data;</div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span>    }</div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span><span class="comment"></span> </div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span><span class="comment">    ///\brief Access to weights as a separate container.</span></div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span><span class="comment"></span>    WeightContainer <span class="keyword">const</span>&amp; weights()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>        <span class="keywordflow">return</span> m_weights;</div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span><span class="comment">    ///\brief Access to weights as a separate container.</span></div>
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno">  284</span><span class="comment"></span>    WeightContainer&amp; weights(){</div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span>        <span class="keywordflow">return</span> m_weights;</div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span>    }</div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span> </div>
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno">  288</span>    <span class="comment">// CONSTRUCTORS</span></div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span><span class="comment"></span> </div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span><span class="comment">    ///\brief Constructs an Empty data set.</span></div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span><span class="comment"></span>    BaseWeightedDataset()</div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span>    {}</div>
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno">  293</span><span class="comment"></span> </div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span><span class="comment">    ///\brief Create an empty set with just the correct number of batches.</span></div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span><span class="comment">    /// The user must initialize the dataset after that by himself.</span></div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span><span class="comment"></span>    BaseWeightedDataset(std::size_t numBatches)</div>
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno">  298</span>    : m_data(numBatches),m_weights(numBatches)</div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span>    {}</div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span><span class="comment"></span> </div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span><span class="comment">    /// \brief Construtor using a single element as blueprint to create a dataset with a specified number of elements.</span></div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span><span class="comment">    /// Optionally the desired batch Size can be set</span></div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span><span class="comment">    ///@param size the new size of the container</span></div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span><span class="comment">    ///@param element the blueprint element from which to create the Container</span></div>
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno">  307</span><span class="comment">    ///@param batchSize the size of the batches. if this is 0, the size is unlimited</span></div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span><span class="comment"></span>    BaseWeightedDataset(std::size_t size, element_type <span class="keyword">const</span>&amp; element, std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>)</div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span>    : m_data(size,element.data,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>)</div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span>    , m_weights(size,element.weight,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>)</div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span>    {}</div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span><span class="comment"></span> </div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span><span class="comment">    ///\brief Construction from data and a dataset rpresnting the weights</span></div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span><span class="comment">    /// Beware that when calling this constructor the organization of batches must be equal in both</span></div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span><span class="comment">    /// containers. This Constructor will not reorganize the data!</span></div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span><span class="comment"></span>    BaseWeightedDataset(DataContainer <span class="keyword">const</span>&amp; data, <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;WeightType&gt;</a> <span class="keyword">const</span>&amp; weights)</div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span>    : m_data(data), m_weights(weights)</div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span>    {</div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span>        <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(data.numberOfElements() == weights.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>(), <span class="stringliteral">&quot;[ BaseWeightedDataset::WeightedUnlabeledData] number of data and number of weights must agree&quot;</span>);</div>
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno">  321</span><span class="preprocessor">#ifndef DNDEBUG</span></div>
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno">  322</span>        <span class="keywordflow">for</span>(std::size_t i  = 0; i != data.numberOfBatches(); ++i){</div>
<div class="line"><a id="l00323" name="l00323"></a><span class="lineno">  323</span>            <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(data.batch(i)) == <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(weights.<a class="code hl_function" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">batch</a>(i)));</div>
<div class="line"><a id="l00324" name="l00324"></a><span class="lineno">  324</span>        }</div>
<div class="line"><a id="l00325" name="l00325"></a><span class="lineno">  325</span><span class="preprocessor">#endif</span></div>
<div class="line"><a id="l00326" name="l00326"></a><span class="lineno">  326</span>    }</div>
<div class="line"><a id="l00327" name="l00327"></a><span class="lineno">  327</span>    <span class="comment"></span></div>
<div class="line"><a id="l00328" name="l00328"></a><span class="lineno">  328</span><span class="comment">    ///\brief Construction from data. All points get the same weight assigned</span></div>
<div class="line"><a id="l00329" name="l00329"></a><span class="lineno">  329</span><span class="comment"></span>    BaseWeightedDataset(DataContainer <span class="keyword">const</span>&amp; data, <span class="keywordtype">double</span> weight)</div>
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno">  330</span>    : m_data(data), m_weights(data.numberOfBatches())</div>
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno">  331</span>    {</div>
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno">  332</span>        <span class="keywordflow">for</span>(std::size_t i = 0; i != numberOfBatches(); ++i){</div>
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno">  333</span>            m_weights.batch(i) = <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;WeightType&gt;::type</a>(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(m_data.batch(i)),weight);</div>
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno">  334</span>        }</div>
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno">  335</span>    }</div>
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno">  336</span>    </div>
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno">  337</span>    </div>
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno">  338</span>    <span class="comment">// ELEMENT ACCESS</span></div>
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno">  339</span>    element_reference element(std::size_t i){</div>
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno">  340</span>        <span class="keywordflow">return</span> *(detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; &gt;(<span class="keyword">this</span>,0,0,0)+i);</div>
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno">  341</span>    }</div>
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno">  342</span>    const_element_reference element(std::size_t i)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno">  343</span>        <span class="keywordflow">return</span> *(detail::DataElementIterator&lt;BaseWeightedDataset&lt;DataContainer&gt; <span class="keyword">const</span>&gt;(<span class="keyword">this</span>,0,0,0)+i);</div>
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno">  344</span>    }</div>
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno">  345</span> </div>
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno">  346</span>    <span class="comment">// BATCH ACCESS</span></div>
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno">  347</span>    batch_reference batch(std::size_t i){</div>
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno">  348</span>        <span class="keywordflow">return</span> batch_reference(m_data.batch(i),m_weights.batch(i));</div>
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno">  349</span>    }</div>
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno">  350</span>    const_batch_reference batch(std::size_t i)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno">  351</span>        <span class="keywordflow">return</span> const_batch_reference(m_data.batch(i),m_weights.batch(i));</div>
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno">  352</span>    }</div>
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno">  353</span> </div>
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno">  354</span>    <span class="comment">// MISC</span></div>
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno">  355</span><span class="comment"></span> </div>
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno">  356</span><span class="comment">    /// from ISerializable</span></div>
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno">  357</span><span class="comment"></span>    <span class="keywordtype">void</span> read(<a class="code hl_typedef" href="namespaceshark.html#ada68729491840669e47c8ad42282424f" title="Type of an archive to read from.">InArchive</a>&amp; archive){</div>
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno">  358</span>        archive &amp; m_data;</div>
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno">  359</span>        archive &amp; m_weights;</div>
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno">  360</span>    }</div>
<div class="line"><a id="l00361" name="l00361"></a><span class="lineno">  361</span><span class="comment"></span> </div>
<div class="line"><a id="l00362" name="l00362"></a><span class="lineno">  362</span><span class="comment">    /// from ISerializable</span></div>
<div class="line"><a id="l00363" name="l00363"></a><span class="lineno">  363</span><span class="comment"></span>    <span class="keywordtype">void</span> write(<a class="code hl_typedef" href="namespaceshark.html#af4f8eb8e9618f5236b71bbcb12b8a524" title="Type of an archive to write to.">OutArchive</a>&amp; archive)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00364" name="l00364"></a><span class="lineno">  364</span>        archive &amp; m_data;</div>
<div class="line"><a id="l00365" name="l00365"></a><span class="lineno">  365</span>        archive &amp; m_weights;</div>
<div class="line"><a id="l00366" name="l00366"></a><span class="lineno">  366</span>    }</div>
<div class="line"><a id="l00367" name="l00367"></a><span class="lineno">  367</span><span class="comment"></span> </div>
<div class="line"><a id="l00368" name="l00368"></a><span class="lineno">  368</span><span class="comment">    ///\brief This method makes the vector independent of all siblings and parents.</span></div>
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno">  369</span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> makeIndependent(){</div>
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno">  370</span>        m_weights.makeIndependent();</div>
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno">  371</span>        m_data.makeIndependent();</div>
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno">  372</span>    }</div>
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno">  373</span><span class="comment"></span> </div>
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno">  374</span><span class="comment">    ///\brief shuffles all elements in the entire dataset (that is, also across the batches)</span></div>
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno">  375</span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#af2ba61b9ed8b5072db8ce9582dcb94b0" title="random_shuffle algorithm which stops after acquiring the random subsequence for [begin,...">shuffle</a>(){</div>
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno">  376</span>        <a class="code hl_function" href="namespaceshark.html#af2ba61b9ed8b5072db8ce9582dcb94b0" title="random_shuffle algorithm which stops after acquiring the random subsequence for [begin,...">shark::shuffle</a>(this-&gt;elements().begin(),this-&gt;elements().end(), <a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>);</div>
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno">  377</span>    }</div>
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno">  378</span> </div>
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno">  379</span>    <span class="keywordtype">void</span> splitBatch(std::size_t batch, std::size_t elementIndex){</div>
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno">  380</span>        m_data.splitBatch(batch,elementIndex);</div>
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno">  381</span>        m_weights.splitBatch(batch,elementIndex);</div>
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno">  382</span>    }</div>
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno">  383</span><span class="comment"></span> </div>
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno">  384</span><span class="comment">    /// \brief Appends the contents of another data object to the end</span></div>
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno">  385</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno">  386</span><span class="comment">    /// The batches are not copied but now referenced from both datasets. Thus changing the appended</span></div>
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno">  387</span><span class="comment">    /// dataset might change this one as well.</span></div>
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno">  388</span><span class="comment"></span>    <span class="keywordtype">void</span> append(BaseWeightedDataset <span class="keyword">const</span>&amp; other){</div>
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno">  389</span>        m_data.append(other.m_data);</div>
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno">  390</span>        m_weights.append(other.m_weights);</div>
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno">  391</span>    }</div>
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno">  392</span> </div>
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno">  393</span><span class="comment"></span> </div>
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno">  394</span><span class="comment">    ///\brief Reorders the batch structure in the container to that indicated by the batchSizes vector</span></div>
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno">  395</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno">  396</span><span class="comment">    ///After the operation the container will contain batchSizes.size() batches with the i-th batch having size batchSize[i].</span></div>
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno">  397</span><span class="comment">    ///However the sum of all batch sizes must be equal to the current number of elements</span></div>
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno">  398</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> Range&gt;</div>
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno">  399</span>    <span class="keywordtype">void</span> repartition(Range <span class="keyword">const</span>&amp; batchSizes){</div>
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno">  400</span>        m_data.repartition(batchSizes);</div>
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno">  401</span>        m_weights.repartition(batchSizes);</div>
<div class="line"><a id="l00402" name="l00402"></a><span class="lineno">  402</span>    }</div>
<div class="line"><a id="l00403" name="l00403"></a><span class="lineno">  403</span>    <span class="comment"></span></div>
<div class="line"><a id="l00404" name="l00404"></a><span class="lineno">  404</span><span class="comment">    /// \brief Creates a vector with the batch sizes of every batch.</span></div>
<div class="line"><a id="l00405" name="l00405"></a><span class="lineno">  405</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00406" name="l00406"></a><span class="lineno">  406</span><span class="comment">    /// This method can be used together with repartition to ensure</span></div>
<div class="line"><a id="l00407" name="l00407"></a><span class="lineno">  407</span><span class="comment">    /// that two datasets have the same batch structure.</span></div>
<div class="line"><a id="l00408" name="l00408"></a><span class="lineno">  408</span><span class="comment"></span>    std::vector&lt;std::size_t&gt; getPartitioning()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00409" name="l00409"></a><span class="lineno">  409</span>        <span class="keywordflow">return</span> m_data.getPartitioning();</div>
<div class="line"><a id="l00410" name="l00410"></a><span class="lineno">  410</span>    }</div>
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno">  411</span> </div>
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno">  412</span>    <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>( BaseWeightedDataset&amp; a, BaseWeightedDataset&amp; b){</div>
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno">  413</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(a.m_data,b.m_data);</div>
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno">  414</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(a.m_weights,b.m_weights);</div>
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno">  415</span>    }</div>
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno">  416</span> </div>
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno">  417</span> </div>
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno">  418</span>    <span class="comment">// SUBSETS</span></div>
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno">  419</span><span class="comment"></span> </div>
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno">  420</span><span class="comment">    ///\brief Fill in the subset defined by the list of indices.</span></div>
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno">  421</span><span class="comment"></span>    BaseWeightedDataset indexedSubset(IndexSet <span class="keyword">const</span>&amp; indices)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno">  422</span>        BaseWeightedDataset <a class="code hl_function" href="group__shark__globals.html#ga420a47af92d8da0f5e95a7d158521db9" title="Creates a subset of a DataView with elements indexed by indices.">subset</a>;</div>
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno">  423</span>        <a class="code hl_function" href="group__shark__globals.html#ga420a47af92d8da0f5e95a7d158521db9" title="Creates a subset of a DataView with elements indexed by indices.">subset</a>.m_data = m_data.indexedSubset(indices);</div>
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno">  424</span>        <a class="code hl_function" href="group__shark__globals.html#ga420a47af92d8da0f5e95a7d158521db9" title="Creates a subset of a DataView with elements indexed by indices.">subset</a>.m_weights = m_weights.indexedSubset(indices);</div>
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno">  425</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga420a47af92d8da0f5e95a7d158521db9" title="Creates a subset of a DataView with elements indexed by indices.">subset</a>;</div>
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno">  426</span>    }</div>
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno">  427</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno">  428</span>    DataContainer m_data;               <span class="comment">/// point data</span></div>
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno">  429</span>    WeightContainer m_weights; <span class="comment">/// weight data</span></div>
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno">  430</span>};</div>
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno">  431</span>}</div>
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno">  432</span><span class="comment"></span> </div>
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno">  433</span><span class="comment">///</span></div>
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno">  434</span><span class="comment">/// \brief Weighted data set for unsupervised learning</span></div>
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno">  435</span><span class="comment">///</span></div>
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno">  436</span><span class="comment">/// The WeightedUnlabeledData class extends UnlabeledData for the</span></div>
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno">  437</span><span class="comment">/// representation of data. In addition it holds and provides access to the corresponding weights.</span></div>
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno">  438</span><span class="comment">///</span></div>
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno">  439</span><span class="comment">/// WeightedUnlabeledData tries to mimic the underlying data as pairs of data points and weights.</span></div>
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno">  440</span><span class="comment">/// this means that when accessing a batch by calling batch(i) or choosing one of the iterators</span></div>
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno">  441</span><span class="comment">/// one access the input batch by batch(i).data and the weights by batch(i).weight</span></div>
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno">  442</span><span class="comment">///</span></div>
<div class="line"><a id="l00443" name="l00443"></a><span class="lineno">  443</span><span class="comment">///this also holds true for single element access using operator(). Be aware, that direct access to element is</span></div>
<div class="line"><a id="l00444" name="l00444"></a><span class="lineno">  444</span><span class="comment">///a linear time operation. So it is not advisable to iterate over the elements, but instead iterate over the batches.</span></div>
<div class="line"><a id="l00445" name="l00445"></a><span class="lineno">  445</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> DataT&gt;</div>
<div class="foldopen" id="foldopen00446" data-start="{" data-end="};">
<div class="line"><a id="l00446" name="l00446"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html">  446</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData</a> : <span class="keyword">public</span> detail::BaseWeightedDataset &lt;UnlabeledData&lt;DataT&gt; &gt;</div>
<div class="line"><a id="l00447" name="l00447"></a><span class="lineno">  447</span>{</div>
<div class="line"><a id="l00448" name="l00448"></a><span class="lineno">  448</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00449" name="l00449"></a><span class="lineno">  449</span>    <span class="keyword">typedef</span> detail::BaseWeightedDataset &lt;UnlabeledData&lt;DataT&gt; &gt; base_type;</div>
<div class="line"><a id="l00450" name="l00450"></a><span class="lineno">  450</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno">  451</span>    <span class="keyword">using </span>base_type::data;</div>
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno">  452</span>    <span class="keyword">using </span>base_type::weights;</div>
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a91d5113d9a6f67a6593d76e4a265cf51">  453</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::DataType <a class="code hl_typedef" href="classshark_1_1_weighted_unlabeled_data.html#a91d5113d9a6f67a6593d76e4a265cf51">DataType</a>;</div>
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a9b55cb78df8d7a45a4bf3d8086f3a65f">  454</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::WeightType <a class="code hl_typedef" href="classshark_1_1_weighted_unlabeled_data.html#a9b55cb78df8d7a45a4bf3d8086f3a65f">WeightType</a>;</div>
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno">  455</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::element_type element_type;</div>
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#aed7e005edba4dee30e735fcac0538f45">  456</a></span>    <span class="keyword">typedef</span> DataT <a class="code hl_typedef" href="classshark_1_1_weighted_unlabeled_data.html#aed7e005edba4dee30e735fcac0538f45">InputType</a>;</div>
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno">  457</span> </div>
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#ad6c78becf3a0a703a506f17d9535e0b9">  458</a></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#ad6c78becf3a0a703a506f17d9535e0b9">BOOST_STATIC_CONSTANT</a>(std::size_t, DefaultBatchSize = <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;DataT&gt;::DefaultBatchSize</a>);</div>
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno">  459</span> </div>
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno">  460</span>    <span class="comment">// CONSTRUCTORS</span></div>
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno">  461</span><span class="comment"></span> </div>
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno">  462</span><span class="comment">    ///\brief Empty data set.</span></div>
<div class="foldopen" id="foldopen00463" data-start="{" data-end="}">
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#ab781cf87de5c135103795a0c44210b2b">  463</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#ab781cf87de5c135103795a0c44210b2b" title="Empty data set.">WeightedUnlabeledData</a>()</div>
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno">  464</span>    {}</div>
</div>
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno">  465</span><span class="comment"></span> </div>
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno">  466</span><span class="comment">    ///\brief Create an empty set with just the correct number of batches.</span></div>
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno">  467</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno">  468</span><span class="comment">    /// The user must initialize the dataset after that by himself.</span></div>
<div class="foldopen" id="foldopen00469" data-start="{" data-end="}">
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a9301c466c82723786aef62ab802a9a55">  469</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a9301c466c82723786aef62ab802a9a55" title="Create an empty set with just the correct number of batches.">WeightedUnlabeledData</a>(std::size_t numBatches)</div>
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno">  470</span>    : base_type(numBatches)</div>
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno">  471</span>    {}</div>
</div>
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno">  472</span><span class="comment"></span> </div>
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno">  473</span><span class="comment">    /// \brief Construtor using a single element as blueprint to create a dataset with a specified number of elements.</span></div>
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno">  474</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno">  475</span><span class="comment">    /// Optionally the desired batch Size can be set</span></div>
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno">  476</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00477" name="l00477"></a><span class="lineno">  477</span><span class="comment">    ///@param size the new size of the container</span></div>
<div class="line"><a id="l00478" name="l00478"></a><span class="lineno">  478</span><span class="comment">    ///@param element the blueprint element from which to create the Container</span></div>
<div class="line"><a id="l00479" name="l00479"></a><span class="lineno">  479</span><span class="comment">    ///@param batchSize the size of the batches. if this is 0, the size is unlimited</span></div>
<div class="foldopen" id="foldopen00480" data-start="{" data-end="}">
<div class="line"><a id="l00480" name="l00480"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#ab16d53abba61cf2bb3af7a4f94c1d85b">  480</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#ab16d53abba61cf2bb3af7a4f94c1d85b" title="Construtor using a single element as blueprint to create a dataset with a specified number of element...">WeightedUnlabeledData</a>(std::size_t size, element_type <span class="keyword">const</span>&amp; element, std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = DefaultBatchSize)</div>
<div class="line"><a id="l00481" name="l00481"></a><span class="lineno">  481</span>    : base_type(size,element,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>){}</div>
</div>
<div class="line"><a id="l00482" name="l00482"></a><span class="lineno">  482</span><span class="comment"></span> </div>
<div class="line"><a id="l00483" name="l00483"></a><span class="lineno">  483</span><span class="comment">    ///\brief Construction from data.</span></div>
<div class="line"><a id="l00484" name="l00484"></a><span class="lineno">  484</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00485" name="l00485"></a><span class="lineno">  485</span><span class="comment">    /// Beware that when calling this constructor the organization of batches must be equal in both</span></div>
<div class="line"><a id="l00486" name="l00486"></a><span class="lineno">  486</span><span class="comment">    /// containers. This Constructor will not reorganize the data!</span></div>
<div class="foldopen" id="foldopen00487" data-start="{" data-end="}">
<div class="line"><a id="l00487" name="l00487"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a29b5ac16bc4687d21baf574641025bf5">  487</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a29b5ac16bc4687d21baf574641025bf5" title="Construction from data.">WeightedUnlabeledData</a>(<a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;DataType&gt;</a> <span class="keyword">const</span>&amp; data, <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;WeightType&gt;</a> <span class="keyword">const</span>&amp; weights)</div>
<div class="line"><a id="l00488" name="l00488"></a><span class="lineno">  488</span>    : base_type(data,weights)</div>
<div class="line"><a id="l00489" name="l00489"></a><span class="lineno">  489</span>    {}</div>
</div>
<div class="line"><a id="l00490" name="l00490"></a><span class="lineno">  490</span>        <span class="comment"></span></div>
<div class="line"><a id="l00491" name="l00491"></a><span class="lineno">  491</span><span class="comment">    ///\brief Construction from data and a constant weight for all elements</span></div>
<div class="foldopen" id="foldopen00492" data-start="{" data-end="}">
<div class="line"><a id="l00492" name="l00492"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#ab5561feeee3c7bbd010c1da83bb7797b">  492</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#ab5561feeee3c7bbd010c1da83bb7797b" title="Construction from data and a constant weight for all elements.">WeightedUnlabeledData</a>(<a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;DataType&gt;</a> <span class="keyword">const</span>&amp; data, <span class="keywordtype">double</span> weight)</div>
<div class="line"><a id="l00493" name="l00493"></a><span class="lineno">  493</span>    : base_type(data,weight)</div>
<div class="line"><a id="l00494" name="l00494"></a><span class="lineno">  494</span>    {}</div>
</div>
<div class="line"><a id="l00495" name="l00495"></a><span class="lineno">  495</span>        </div>
<div class="line"><a id="l00496" name="l00496"></a><span class="lineno">  496</span>    <span class="comment">//we additionally add the two below for compatibility with UnlabeledData</span></div>
<div class="line"><a id="l00497" name="l00497"></a><span class="lineno">  497</span>        <span class="comment"></span></div>
<div class="line"><a id="l00498" name="l00498"></a><span class="lineno">  498</span><span class="comment">    ///\brief Access to the inputs as a separate container.</span></div>
<div class="foldopen" id="foldopen00499" data-start="{" data-end="}">
<div class="line"><a id="l00499" name="l00499"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#af30cf1f800bf899e55de467f9e211b52">  499</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;DataT&gt;</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#af30cf1f800bf899e55de467f9e211b52" title="Access to the inputs as a separate container.">inputs</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00500" name="l00500"></a><span class="lineno">  500</span>        <span class="keywordflow">return</span> data();</div>
<div class="line"><a id="l00501" name="l00501"></a><span class="lineno">  501</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00502" name="l00502"></a><span class="lineno">  502</span><span class="comment">    ///\brief Access to the inputs as a separate container.</span></div>
<div class="foldopen" id="foldopen00503" data-start="{" data-end="}">
<div class="line"><a id="l00503" name="l00503"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a40369ede148f5687ac274a7f6816809c">  503</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;DataT&gt;</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a40369ede148f5687ac274a7f6816809c" title="Access to the inputs as a separate container.">inputs</a>(){</div>
<div class="line"><a id="l00504" name="l00504"></a><span class="lineno">  504</span>        <span class="keywordflow">return</span> data();</div>
<div class="line"><a id="l00505" name="l00505"></a><span class="lineno">  505</span>    }</div>
</div>
<div class="line"><a id="l00506" name="l00506"></a><span class="lineno">  506</span>    <span class="comment"></span></div>
<div class="line"><a id="l00507" name="l00507"></a><span class="lineno">  507</span><span class="comment">    ///\brief Returns the Shape of the data.</span></div>
<div class="foldopen" id="foldopen00508" data-start="{" data-end="}">
<div class="line"><a id="l00508" name="l00508"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a928b2414d9a32987c3341743dc0716e4">  508</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a928b2414d9a32987c3341743dc0716e4" title="Returns the Shape of the data.">shape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00509" name="l00509"></a><span class="lineno">  509</span>        <span class="keywordflow">return</span> data().shape();</div>
<div class="line"><a id="l00510" name="l00510"></a><span class="lineno">  510</span>    }</div>
</div>
<div class="line"><a id="l00511" name="l00511"></a><span class="lineno">  511</span>    <span class="comment"></span></div>
<div class="line"><a id="l00512" name="l00512"></a><span class="lineno">  512</span><span class="comment">    ///\brief Returns the Shape of the data.</span></div>
<div class="foldopen" id="foldopen00513" data-start="{" data-end="}">
<div class="line"><a id="l00513" name="l00513"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a58475c3c9b0480c96397c771a4a1759f">  513</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a58475c3c9b0480c96397c771a4a1759f" title="Returns the Shape of the data.">shape</a>(){</div>
<div class="line"><a id="l00514" name="l00514"></a><span class="lineno">  514</span>        <span class="keywordflow">return</span> data().shape();</div>
<div class="line"><a id="l00515" name="l00515"></a><span class="lineno">  515</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00516" name="l00516"></a><span class="lineno">  516</span><span class="comment">    ///\brief Splits the container into two independent parts. The left part remains in the container, the right is stored as return type</span></div>
<div class="line"><a id="l00517" name="l00517"></a><span class="lineno">  517</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00518" name="l00518"></a><span class="lineno">  518</span><span class="comment">    ///Order of elements remain unchanged. The SharedVector is not allowed to be shared for</span></div>
<div class="line"><a id="l00519" name="l00519"></a><span class="lineno">  519</span><span class="comment">    ///this to work.</span></div>
<div class="foldopen" id="foldopen00520" data-start="{" data-end="}">
<div class="line"><a id="l00520" name="l00520"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#a71bcad4364057b3d20b6315176d6b480">  520</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData</a> <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a71bcad4364057b3d20b6315176d6b480" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(std::size_t batch){</div>
<div class="line"><a id="l00521" name="l00521"></a><span class="lineno">  521</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#ab781cf87de5c135103795a0c44210b2b" title="Empty data set.">WeightedUnlabeledData</a>(data().<a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a71bcad4364057b3d20b6315176d6b480" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(batch),weights().<a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a71bcad4364057b3d20b6315176d6b480" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(batch));</div>
<div class="line"><a id="l00522" name="l00522"></a><span class="lineno">  522</span>    }</div>
</div>
<div class="line"><a id="l00523" name="l00523"></a><span class="lineno">  523</span> </div>
<div class="foldopen" id="foldopen00524" data-start="{" data-end="};">
<div class="line"><a id="l00524" name="l00524"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_unlabeled_data.html#aac37ab4ee3db2b92d744146f176b43c2">  524</a></span>    <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code hl_friend" href="classshark_1_1_weighted_unlabeled_data.html#aac37ab4ee3db2b92d744146f176b43c2">swap</a>(<a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData</a>&amp; a, <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData</a>&amp; b){</div>
<div class="line"><a id="l00525" name="l00525"></a><span class="lineno">  525</span>        <a class="code hl_friend" href="classshark_1_1_weighted_unlabeled_data.html#aac37ab4ee3db2b92d744146f176b43c2">swap</a>(<span class="keyword">static_cast&lt;</span>base_type&amp;<span class="keyword">&gt;</span>(a),<span class="keyword">static_cast&lt;</span>base_type&amp;<span class="keyword">&gt;</span>(b));</div>
<div class="line"><a id="l00526" name="l00526"></a><span class="lineno">  526</span>    }</div>
</div>
<div class="line"><a id="l00527" name="l00527"></a><span class="lineno">  527</span>};</div>
</div>
<div class="line"><a id="l00528" name="l00528"></a><span class="lineno">  528</span><span class="comment"></span> </div>
<div class="line"><a id="l00529" name="l00529"></a><span class="lineno">  529</span><span class="comment">///brief  Outstream of elements for weighted data.</span></div>
<div class="line"><a id="l00530" name="l00530"></a><span class="lineno">  530</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T&gt;</div>
<div class="foldopen" id="foldopen00531" data-start="{" data-end="}">
<div class="line"><a id="l00531" name="l00531"></a><span class="lineno"><a class="line" href="namespaceshark.html#ae649311a310e6840b33c08f9cc2c78a7">  531</a></span>std::ostream &amp;<a class="code hl_function" href="namespaceshark.html#a09ff8eea9690a4f7c082d545d1ba997b">operator &lt;&lt; </a>(std::ostream &amp;stream, <span class="keyword">const</span> <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;T&gt;</a>&amp; d) {</div>
<div class="line"><a id="l00532" name="l00532"></a><span class="lineno">  532</span>    <span class="keywordflow">for</span>(<span class="keyword">auto</span> elem: d.elements())</div>
<div class="line"><a id="l00533" name="l00533"></a><span class="lineno">  533</span>        stream &lt;&lt; elem.weight &lt;&lt; <span class="stringliteral">&quot; [&quot;</span> &lt;&lt; elem.data&lt;&lt;<span class="stringliteral">&quot;]&quot;</span>&lt;&lt; <span class="stringliteral">&quot;\n&quot;</span>;</div>
<div class="line"><a id="l00534" name="l00534"></a><span class="lineno">  534</span>    <span class="keywordflow">return</span> stream;</div>
<div class="line"><a id="l00535" name="l00535"></a><span class="lineno">  535</span>}</div>
</div>
<div class="line"><a id="l00536" name="l00536"></a><span class="lineno">  536</span><span class="comment"></span> </div>
<div class="line"><a id="l00537" name="l00537"></a><span class="lineno">  537</span><span class="comment">/// \brief creates a weighted unweighted data object from two ranges, representing data and weights</span></div>
<div class="line"><a id="l00538" name="l00538"></a><span class="lineno">  538</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DataRange, <span class="keyword">class</span> WeightRange&gt;</div>
<div class="line"><a id="l00539" name="l00539"></a><span class="lineno">  539</span><span class="keyword">typename</span> boost::disable_if&lt;</div>
<div class="line"><a id="l00540" name="l00540"></a><span class="lineno">  540</span>    boost::is_arithmetic&lt;WeightRange&gt;,</div>
<div class="line"><a id="l00541" name="l00541"></a><span class="lineno">  541</span>    WeightedUnlabeledData&lt;</div>
<div class="line"><a id="l00542" name="l00542"></a><span class="lineno">  542</span>        <span class="keyword">typename</span> boost::range_value&lt;DataRange&gt;::type</div>
<div class="line"><a id="l00543" name="l00543"></a><span class="lineno">  543</span>    &gt; </div>
<div class="foldopen" id="foldopen00544" data-start="{" data-end="}">
<div class="line"><a id="l00544" name="l00544"></a><span class="lineno"><a class="line" href="namespaceshark.html#ad9ed735e63f102b04c82053f8f2922f0">  544</a></span>&gt;::type <a class="code hl_function" href="group__shark__globals.html#ga28f4e36576738062f68ba0ca3e0033be" title="creates a data object from a range of elements">createUnlabeledDataFromRange</a>(DataRange <span class="keyword">const</span>&amp; data, WeightRange <span class="keyword">const</span>&amp; weights, std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = 0){</div>
<div class="line"><a id="l00545" name="l00545"></a><span class="lineno">  545</span> </div>
<div class="line"><a id="l00546" name="l00546"></a><span class="lineno">  546</span>    <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(data) == <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(weights),<span class="stringliteral">&quot;Number of datapoints and number of weights must agree&quot;</span>);</div>
<div class="line"><a id="l00547" name="l00547"></a><span class="lineno">  547</span> </div>
<div class="line"><a id="l00548" name="l00548"></a><span class="lineno">  548</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> boost::range_value&lt;DataRange&gt;::type <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data</a>;</div>
<div class="line"><a id="l00549" name="l00549"></a><span class="lineno">  549</span> </div>
<div class="line"><a id="l00550" name="l00550"></a><span class="lineno">  550</span>    <span class="keywordflow">if</span> (<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> == 0)</div>
<div class="line"><a id="l00551" name="l00551"></a><span class="lineno">  551</span>        <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;Data&gt;::DefaultBatchSize</a>;</div>
<div class="line"><a id="l00552" name="l00552"></a><span class="lineno">  552</span> </div>
<div class="line"><a id="l00553" name="l00553"></a><span class="lineno">  553</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;Data&gt;</a>(</div>
<div class="line"><a id="l00554" name="l00554"></a><span class="lineno">  554</span>        <a class="code hl_function" href="group__shark__globals.html#ga28f4e36576738062f68ba0ca3e0033be" title="creates a data object from a range of elements">shark::createUnlabeledDataFromRange</a>(data,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>),</div>
<div class="line"><a id="l00555" name="l00555"></a><span class="lineno">  555</span>        <a class="code hl_function" href="group__shark__globals.html#ga1a1a4f4249f709e6169a601a9a857fa8" title="creates a data object from a range of elements">createDataFromRange</a>(weights,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>)</div>
<div class="line"><a id="l00556" name="l00556"></a><span class="lineno">  556</span>    );</div>
<div class="line"><a id="l00557" name="l00557"></a><span class="lineno">  557</span>}</div>
</div>
<div class="line"><a id="l00558" name="l00558"></a><span class="lineno">  558</span> </div>
<div class="line"><a id="l00559" name="l00559"></a><span class="lineno">  559</span><span class="comment"></span> </div>
<div class="line"><a id="l00560" name="l00560"></a><span class="lineno">  560</span><span class="comment">///</span></div>
<div class="line"><a id="l00561" name="l00561"></a><span class="lineno">  561</span><span class="comment">/// \brief Weighted data set for supervised learning</span></div>
<div class="line"><a id="l00562" name="l00562"></a><span class="lineno">  562</span><span class="comment">///</span></div>
<div class="line"><a id="l00563" name="l00563"></a><span class="lineno">  563</span><span class="comment">/// The WeightedLabeledData class extends LabeledData for the</span></div>
<div class="line"><a id="l00564" name="l00564"></a><span class="lineno">  564</span><span class="comment">/// representation of data. In addition it holds and provides access to the corresponding weights.</span></div>
<div class="line"><a id="l00565" name="l00565"></a><span class="lineno">  565</span><span class="comment">///</span></div>
<div class="line"><a id="l00566" name="l00566"></a><span class="lineno">  566</span><span class="comment">/// WeightedLabeledData tries to mimic the underlying data as pairs of data tuples(input,label) and weights.</span></div>
<div class="line"><a id="l00567" name="l00567"></a><span class="lineno">  567</span><span class="comment">/// this means that when accessing a batch by calling batch(i) or choosing one of the iterators</span></div>
<div class="line"><a id="l00568" name="l00568"></a><span class="lineno">  568</span><span class="comment">/// one access the databatch by batch(i).data and the weights by batch(i).weight. to access the points and labels</span></div>
<div class="line"><a id="l00569" name="l00569"></a><span class="lineno">  569</span><span class="comment">/// use batch(i).data.input and batch(i).data.label</span></div>
<div class="line"><a id="l00570" name="l00570"></a><span class="lineno">  570</span><span class="comment">///</span></div>
<div class="line"><a id="l00571" name="l00571"></a><span class="lineno">  571</span><span class="comment">///this also holds true for single element access using operator(). Be aware, that direct access to element is</span></div>
<div class="line"><a id="l00572" name="l00572"></a><span class="lineno">  572</span><span class="comment">///a linear time operation. So it is not advisable to iterate over the elements, but instead iterate over the batches.</span></div>
<div class="line"><a id="l00573" name="l00573"></a><span class="lineno">  573</span><span class="comment">///</span></div>
<div class="line"><a id="l00574" name="l00574"></a><span class="lineno">  574</span><span class="comment">/// It is possible to gains everal views on the set. one can either get access to inputs, labels and weights separately</span></div>
<div class="line"><a id="l00575" name="l00575"></a><span class="lineno">  575</span><span class="comment">/// or gain access to the unweighted dataset of inputs and labels. Additionally the sets support on-the-fly creation</span></div>
<div class="line"><a id="l00576" name="l00576"></a><span class="lineno">  576</span><span class="comment">/// of the (inputs,weights) subset for unsupervised weighted learning</span></div>
<div class="line"><a id="l00577" name="l00577"></a><span class="lineno">  577</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> InputT, <span class="keyword">class</span> LabelT&gt;</div>
<div class="foldopen" id="foldopen00578" data-start="{" data-end="};">
<div class="line"><a id="l00578" name="l00578"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html">  578</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData</a> : <span class="keyword">public</span> detail::BaseWeightedDataset &lt;LabeledData&lt;InputT,LabelT&gt; &gt;</div>
<div class="line"><a id="l00579" name="l00579"></a><span class="lineno">  579</span>{</div>
<div class="line"><a id="l00580" name="l00580"></a><span class="lineno">  580</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00581" name="l00581"></a><span class="lineno">  581</span>    <span class="keyword">typedef</span> detail::BaseWeightedDataset &lt;LabeledData&lt;InputT,LabelT&gt; &gt; base_type;</div>
<div class="line"><a id="l00582" name="l00582"></a><span class="lineno">  582</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00583" name="l00583"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a281b253f885a39cf0f7b4b536f477850">  583</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::DataType <a class="code hl_typedef" href="classshark_1_1_weighted_labeled_data.html#a281b253f885a39cf0f7b4b536f477850">DataType</a>;</div>
<div class="line"><a id="l00584" name="l00584"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a021e24cd4fb958820ae16690bf5e70a5">  584</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::WeightType <a class="code hl_typedef" href="classshark_1_1_weighted_labeled_data.html#a021e24cd4fb958820ae16690bf5e70a5">WeightType</a>;</div>
<div class="line"><a id="l00585" name="l00585"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#afaf3abc446e7ebb81ca857d73a34a28b">  585</a></span>    <span class="keyword">typedef</span> InputT <a class="code hl_typedef" href="classshark_1_1_weighted_labeled_data.html#afaf3abc446e7ebb81ca857d73a34a28b">InputType</a>;</div>
<div class="line"><a id="l00586" name="l00586"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#adf3341286338d8fcd8789fb7a0a2ef77">  586</a></span>    <span class="keyword">typedef</span> LabelT <a class="code hl_typedef" href="classshark_1_1_weighted_labeled_data.html#adf3341286338d8fcd8789fb7a0a2ef77">LabelType</a>;</div>
<div class="line"><a id="l00587" name="l00587"></a><span class="lineno">  587</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> base_type::element_type element_type;</div>
<div class="line"><a id="l00588" name="l00588"></a><span class="lineno">  588</span> </div>
<div class="line"><a id="l00589" name="l00589"></a><span class="lineno">  589</span>    <span class="keyword">using </span>base_type::data;</div>
<div class="line"><a id="l00590" name="l00590"></a><span class="lineno">  590</span>    <span class="keyword">using </span>base_type::weights;</div>
<div class="line"><a id="l00591" name="l00591"></a><span class="lineno">  591</span> </div>
<div class="line"><a id="l00592" name="l00592"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#af260c63209f6881849b736c91fc000d3">  592</a></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#af260c63209f6881849b736c91fc000d3">BOOST_STATIC_CONSTANT</a>(std::size_t, DefaultBatchSize = (<a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputT,LabelT&gt;::DefaultBatchSize</a>));</div>
<div class="line"><a id="l00593" name="l00593"></a><span class="lineno">  593</span> </div>
<div class="line"><a id="l00594" name="l00594"></a><span class="lineno">  594</span>    <span class="comment">// CONSTRUCTORS</span></div>
<div class="line"><a id="l00595" name="l00595"></a><span class="lineno">  595</span><span class="comment"></span> </div>
<div class="line"><a id="l00596" name="l00596"></a><span class="lineno">  596</span><span class="comment">    ///\brief Empty data set.</span></div>
<div class="foldopen" id="foldopen00597" data-start="{" data-end="}">
<div class="line"><a id="l00597" name="l00597"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a0604b2b664701ba0cfc78c32e43e9f6c">  597</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a0604b2b664701ba0cfc78c32e43e9f6c" title="Empty data set.">WeightedLabeledData</a>()</div>
<div class="line"><a id="l00598" name="l00598"></a><span class="lineno">  598</span>    {}</div>
</div>
<div class="line"><a id="l00599" name="l00599"></a><span class="lineno">  599</span><span class="comment"></span> </div>
<div class="line"><a id="l00600" name="l00600"></a><span class="lineno">  600</span><span class="comment">    ///\brief Create an empty set with just the correct number of batches.</span></div>
<div class="line"><a id="l00601" name="l00601"></a><span class="lineno">  601</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00602" name="l00602"></a><span class="lineno">  602</span><span class="comment">    /// The user must initialize the dataset after that by himself.</span></div>
<div class="foldopen" id="foldopen00603" data-start="{" data-end="}">
<div class="line"><a id="l00603" name="l00603"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a9354b6293662952c09c0d16ccfe9c263">  603</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a9354b6293662952c09c0d16ccfe9c263" title="Create an empty set with just the correct number of batches.">WeightedLabeledData</a>(std::size_t numBatches)</div>
<div class="line"><a id="l00604" name="l00604"></a><span class="lineno">  604</span>    : base_type(numBatches)</div>
<div class="line"><a id="l00605" name="l00605"></a><span class="lineno">  605</span>    {}</div>
</div>
<div class="line"><a id="l00606" name="l00606"></a><span class="lineno">  606</span><span class="comment"></span> </div>
<div class="line"><a id="l00607" name="l00607"></a><span class="lineno">  607</span><span class="comment">    /// \brief Construtor using a single element as blueprint to create a dataset with a specified number of elements.</span></div>
<div class="line"><a id="l00608" name="l00608"></a><span class="lineno">  608</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00609" name="l00609"></a><span class="lineno">  609</span><span class="comment">    /// Optionally the desired batch Size can be set</span></div>
<div class="line"><a id="l00610" name="l00610"></a><span class="lineno">  610</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00611" name="l00611"></a><span class="lineno">  611</span><span class="comment">    ///@param size the new size of the container</span></div>
<div class="line"><a id="l00612" name="l00612"></a><span class="lineno">  612</span><span class="comment">    ///@param element the blueprint element from which to create the Container</span></div>
<div class="line"><a id="l00613" name="l00613"></a><span class="lineno">  613</span><span class="comment">    ///@param batchSize the size of the batches. if this is 0, the size is unlimited</span></div>
<div class="foldopen" id="foldopen00614" data-start="{" data-end="}">
<div class="line"><a id="l00614" name="l00614"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#abe967a168c030e74c18505403215076b">  614</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#abe967a168c030e74c18505403215076b" title="Construtor using a single element as blueprint to create a dataset with a specified number of element...">WeightedLabeledData</a>(std::size_t size, element_type <span class="keyword">const</span>&amp; element, std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = DefaultBatchSize)</div>
<div class="line"><a id="l00615" name="l00615"></a><span class="lineno">  615</span>    : base_type(size,element,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>){}</div>
</div>
<div class="line"><a id="l00616" name="l00616"></a><span class="lineno">  616</span><span class="comment"></span> </div>
<div class="line"><a id="l00617" name="l00617"></a><span class="lineno">  617</span><span class="comment">    ///\brief Construction from data.</span></div>
<div class="line"><a id="l00618" name="l00618"></a><span class="lineno">  618</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00619" name="l00619"></a><span class="lineno">  619</span><span class="comment">    /// Beware that when calling this constructor the organization of batches must be equal in both</span></div>
<div class="line"><a id="l00620" name="l00620"></a><span class="lineno">  620</span><span class="comment">    /// containers. This Constructor will not reorganize the data!</span></div>
<div class="foldopen" id="foldopen00621" data-start="{" data-end="}">
<div class="line"><a id="l00621" name="l00621"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a6c1ca9174edeae5642fcf786700c0418">  621</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a6c1ca9174edeae5642fcf786700c0418" title="Construction from data.">WeightedLabeledData</a>(<a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType,LabelType&gt;</a> <span class="keyword">const</span>&amp; data, <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;WeightType&gt;</a> <span class="keyword">const</span>&amp; weights)</div>
<div class="line"><a id="l00622" name="l00622"></a><span class="lineno">  622</span>    : base_type(data,weights)</div>
<div class="line"><a id="l00623" name="l00623"></a><span class="lineno">  623</span>    {}</div>
</div>
<div class="line"><a id="l00624" name="l00624"></a><span class="lineno">  624</span>        <span class="comment"></span></div>
<div class="line"><a id="l00625" name="l00625"></a><span class="lineno">  625</span><span class="comment">    ///\brief Construction from data and a constant weight for all elements</span></div>
<div class="foldopen" id="foldopen00626" data-start="{" data-end="}">
<div class="line"><a id="l00626" name="l00626"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a6d36f2bcbae5f6fae1b5896c603f44e2">  626</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a6d36f2bcbae5f6fae1b5896c603f44e2" title="Construction from data and a constant weight for all elements.">WeightedLabeledData</a>(<a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType,LabelType&gt;</a> <span class="keyword">const</span>&amp; data, <span class="keywordtype">double</span> weight)</div>
<div class="line"><a id="l00627" name="l00627"></a><span class="lineno">  627</span>    : base_type(data,weight)</div>
<div class="line"><a id="l00628" name="l00628"></a><span class="lineno">  628</span>    {}</div>
</div>
<div class="line"><a id="l00629" name="l00629"></a><span class="lineno">  629</span>        <span class="comment"></span></div>
<div class="line"><a id="l00630" name="l00630"></a><span class="lineno">  630</span><span class="comment">    ///\brief Access to the inputs as a separate container.</span></div>
<div class="foldopen" id="foldopen00631" data-start="{" data-end="}">
<div class="line"><a id="l00631" name="l00631"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead">  631</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;InputType&gt;</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead" title="Access to the inputs as a separate container.">inputs</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00632" name="l00632"></a><span class="lineno">  632</span>        <span class="keywordflow">return</span> data().<a class="code hl_function" href="group__shark__globals.html#gaa539b482e46b278300d34502c579c51a" title="Access to the base_type class as &quot;inputs&quot;.">inputs</a>();</div>
<div class="line"><a id="l00633" name="l00633"></a><span class="lineno">  633</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00634" name="l00634"></a><span class="lineno">  634</span><span class="comment">    ///\brief Access to the inputs as a separate container.</span></div>
<div class="foldopen" id="foldopen00635" data-start="{" data-end="}">
<div class="line"><a id="l00635" name="l00635"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a6ea4cdf11829c2b6f2ca487859f6e617">  635</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;InputType&gt;</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a6ea4cdf11829c2b6f2ca487859f6e617" title="Access to the inputs as a separate container.">inputs</a>(){</div>
<div class="line"><a id="l00636" name="l00636"></a><span class="lineno">  636</span>        <span class="keywordflow">return</span> data().<a class="code hl_function" href="group__shark__globals.html#gaa539b482e46b278300d34502c579c51a" title="Access to the base_type class as &quot;inputs&quot;.">inputs</a>();</div>
<div class="line"><a id="l00637" name="l00637"></a><span class="lineno">  637</span>    }</div>
</div>
<div class="line"><a id="l00638" name="l00638"></a><span class="lineno">  638</span>    <span class="comment"></span></div>
<div class="line"><a id="l00639" name="l00639"></a><span class="lineno">  639</span><span class="comment">    ///\brief Access to the labels as a separate container.</span></div>
<div class="foldopen" id="foldopen00640" data-start="{" data-end="}">
<div class="line"><a id="l00640" name="l00640"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136">  640</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;LabelType&gt;</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00641" name="l00641"></a><span class="lineno">  641</span>        <span class="keywordflow">return</span> data().labels();</div>
<div class="line"><a id="l00642" name="l00642"></a><span class="lineno">  642</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00643" name="l00643"></a><span class="lineno">  643</span><span class="comment">    ///\brief Access to the labels as a separate container.</span></div>
<div class="foldopen" id="foldopen00644" data-start="{" data-end="}">
<div class="line"><a id="l00644" name="l00644"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a9e8d5d55cc570a4a8cfb8418ccfa1587">  644</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;LabelType&gt;</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a9e8d5d55cc570a4a8cfb8418ccfa1587" title="Access to the labels as a separate container.">labels</a>(){</div>
<div class="line"><a id="l00645" name="l00645"></a><span class="lineno">  645</span>        <span class="keywordflow">return</span> data().labels();</div>
<div class="line"><a id="l00646" name="l00646"></a><span class="lineno">  646</span>    }</div>
</div>
<div class="line"><a id="l00647" name="l00647"></a><span class="lineno">  647</span>    <span class="comment"></span></div>
<div class="line"><a id="l00648" name="l00648"></a><span class="lineno">  648</span><span class="comment">    ///\brief Returns the Shape of the inputs.</span></div>
<div class="foldopen" id="foldopen00649" data-start="{" data-end="}">
<div class="line"><a id="l00649" name="l00649"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a4b369aa6cfa440ecb7f5a150e645a2a9">  649</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a4b369aa6cfa440ecb7f5a150e645a2a9" title="Returns the Shape of the inputs.">inputShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00650" name="l00650"></a><span class="lineno">  650</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead" title="Access to the inputs as a separate container.">inputs</a>().<a class="code hl_function" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37" title="Returns the shape of the elements in the dataset.">shape</a>();</div>
<div class="line"><a id="l00651" name="l00651"></a><span class="lineno">  651</span>    }</div>
</div>
<div class="line"><a id="l00652" name="l00652"></a><span class="lineno">  652</span>    <span class="comment"></span></div>
<div class="line"><a id="l00653" name="l00653"></a><span class="lineno">  653</span><span class="comment">    ///\brief Returns the Shape of the inputs.</span></div>
<div class="foldopen" id="foldopen00654" data-start="{" data-end="}">
<div class="line"><a id="l00654" name="l00654"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a78fdd89eae099be245faff5907baa867">  654</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a78fdd89eae099be245faff5907baa867" title="Returns the Shape of the inputs.">inputShape</a>(){</div>
<div class="line"><a id="l00655" name="l00655"></a><span class="lineno">  655</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead" title="Access to the inputs as a separate container.">inputs</a>().<a class="code hl_function" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37" title="Returns the shape of the elements in the dataset.">shape</a>();</div>
<div class="line"><a id="l00656" name="l00656"></a><span class="lineno">  656</span>    }</div>
</div>
<div class="line"><a id="l00657" name="l00657"></a><span class="lineno">  657</span>    <span class="comment"></span></div>
<div class="line"><a id="l00658" name="l00658"></a><span class="lineno">  658</span><span class="comment">    ///\brief Returns the Shape of the labels.</span></div>
<div class="foldopen" id="foldopen00659" data-start="{" data-end="}">
<div class="line"><a id="l00659" name="l00659"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#ab551802a4a3d30b09984ee7c92ca64b5">  659</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ab551802a4a3d30b09984ee7c92ca64b5" title="Returns the Shape of the labels.">labelShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00660" name="l00660"></a><span class="lineno">  660</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>().<a class="code hl_function" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37" title="Returns the shape of the elements in the dataset.">shape</a>();</div>
<div class="line"><a id="l00661" name="l00661"></a><span class="lineno">  661</span>    }</div>
</div>
<div class="line"><a id="l00662" name="l00662"></a><span class="lineno">  662</span>    <span class="comment"></span></div>
<div class="line"><a id="l00663" name="l00663"></a><span class="lineno">  663</span><span class="comment">    ///\brief Returns the Shape of the labels.</span></div>
<div class="foldopen" id="foldopen00664" data-start="{" data-end="}">
<div class="line"><a id="l00664" name="l00664"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a5f6639432fcc7498e0cbb4e74a956ab6">  664</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a>&amp; <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a5f6639432fcc7498e0cbb4e74a956ab6" title="Returns the Shape of the labels.">labelShape</a>(){</div>
<div class="line"><a id="l00665" name="l00665"></a><span class="lineno">  665</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>().<a class="code hl_function" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37" title="Returns the shape of the elements in the dataset.">shape</a>();</div>
<div class="line"><a id="l00666" name="l00666"></a><span class="lineno">  666</span>    }</div>
</div>
<div class="line"><a id="l00667" name="l00667"></a><span class="lineno">  667</span>    <span class="comment"></span></div>
<div class="line"><a id="l00668" name="l00668"></a><span class="lineno">  668</span><span class="comment">    /// \brief Constructs an WeightedUnlabeledData object for the inputs.</span></div>
<div class="foldopen" id="foldopen00669" data-start="{" data-end="}">
<div class="line"><a id="l00669" name="l00669"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a8fe95c73b1014c9e73a377ce6ede962c">  669</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a8fe95c73b1014c9e73a377ce6ede962c" title="Constructs an WeightedUnlabeledData object for the inputs.">weightedInputs</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00670" name="l00670"></a><span class="lineno">  670</span>        <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a>(data().<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead" title="Access to the inputs as a separate container.">inputs</a>(),weights());</div>
<div class="line"><a id="l00671" name="l00671"></a><span class="lineno">  671</span>    }</div>
</div>
<div class="line"><a id="l00672" name="l00672"></a><span class="lineno">  672</span><span class="comment"></span> </div>
<div class="line"><a id="l00673" name="l00673"></a><span class="lineno">  673</span><span class="comment">    ///\brief Splits the container into two independent parts. The left part remains in the container, the right is stored as return type</span></div>
<div class="line"><a id="l00674" name="l00674"></a><span class="lineno">  674</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00675" name="l00675"></a><span class="lineno">  675</span><span class="comment">    ///Order of elements remain unchanged. The SharedVector is not allowed to be shared for</span></div>
<div class="line"><a id="l00676" name="l00676"></a><span class="lineno">  676</span><span class="comment">    ///this to work.</span></div>
<div class="foldopen" id="foldopen00677" data-start="{" data-end="}">
<div class="line"><a id="l00677" name="l00677"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a648fe695e393366e70092d2d80cd4f62">  677</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData</a> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a648fe695e393366e70092d2d80cd4f62" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(std::size_t batch){</div>
<div class="line"><a id="l00678" name="l00678"></a><span class="lineno">  678</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a0604b2b664701ba0cfc78c32e43e9f6c" title="Empty data set.">WeightedLabeledData</a>(data().<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a648fe695e393366e70092d2d80cd4f62" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(batch),weights().<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a648fe695e393366e70092d2d80cd4f62" title="Splits the container into two independent parts. The left part remains in the container,...">splice</a>(batch));</div>
<div class="line"><a id="l00679" name="l00679"></a><span class="lineno">  679</span>    }</div>
</div>
<div class="line"><a id="l00680" name="l00680"></a><span class="lineno">  680</span> </div>
<div class="foldopen" id="foldopen00681" data-start="{" data-end="};">
<div class="line"><a id="l00681" name="l00681"></a><span class="lineno"><a class="line" href="classshark_1_1_weighted_labeled_data.html#a3379551f7a879a2ed49dd6046024dcf3">  681</a></span>    <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code hl_friend" href="classshark_1_1_weighted_labeled_data.html#a3379551f7a879a2ed49dd6046024dcf3">swap</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData</a>&amp; a, <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData</a>&amp; b){</div>
<div class="line"><a id="l00682" name="l00682"></a><span class="lineno">  682</span>        <a class="code hl_friend" href="classshark_1_1_weighted_labeled_data.html#a3379551f7a879a2ed49dd6046024dcf3">swap</a>(<span class="keyword">static_cast&lt;</span>base_type&amp;<span class="keyword">&gt;</span>(a),<span class="keyword">static_cast&lt;</span>base_type&amp;<span class="keyword">&gt;</span>(b));</div>
<div class="line"><a id="l00683" name="l00683"></a><span class="lineno">  683</span>    }</div>
</div>
<div class="line"><a id="l00684" name="l00684"></a><span class="lineno">  684</span>};</div>
</div>
<div class="line"><a id="l00685" name="l00685"></a><span class="lineno">  685</span><span class="comment"></span> </div>
<div class="line"><a id="l00686" name="l00686"></a><span class="lineno">  686</span><span class="comment">///brief  Outstream of elements for weighted labeled data.</span></div>
<div class="line"><a id="l00687" name="l00687"></a><span class="lineno">  687</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> U&gt;</div>
<div class="foldopen" id="foldopen00688" data-start="{" data-end="}">
<div class="line"><a id="l00688" name="l00688"></a><span class="lineno"><a class="line" href="namespaceshark.html#a43da6edbb8021ade0e05ec0f0e8345dd">  688</a></span>std::ostream &amp;<a class="code hl_function" href="namespaceshark.html#a09ff8eea9690a4f7c082d545d1ba997b">operator &lt;&lt; </a>(std::ostream &amp;stream, <span class="keyword">const</span> <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;T, U&gt;</a>&amp; d) {</div>
<div class="line"><a id="l00689" name="l00689"></a><span class="lineno">  689</span>    <span class="keywordflow">for</span>(<span class="keyword">auto</span> elem: d.elements())</div>
<div class="line"><a id="l00690" name="l00690"></a><span class="lineno">  690</span>        stream &lt;&lt; elem.weight &lt;&lt;<span class="stringliteral">&quot; (&quot;</span>&lt;&lt; elem.data.label &lt;&lt; <span class="stringliteral">&quot; [&quot;</span> &lt;&lt; elem.data.input&lt;&lt;<span class="stringliteral">&quot;] )&quot;</span>&lt;&lt; <span class="stringliteral">&quot;\n&quot;</span>;</div>
<div class="line"><a id="l00691" name="l00691"></a><span class="lineno">  691</span>    <span class="keywordflow">return</span> stream;</div>
<div class="line"><a id="l00692" name="l00692"></a><span class="lineno">  692</span>}</div>
</div>
<div class="line"><a id="l00693" name="l00693"></a><span class="lineno">  693</span> </div>
<div class="line"><a id="l00694" name="l00694"></a><span class="lineno">  694</span><span class="comment">//Stuff for Dimensionality and querying of basic information</span></div>
<div class="line"><a id="l00695" name="l00695"></a><span class="lineno">  695</span> </div>
<div class="foldopen" id="foldopen00696" data-start="{" data-end="}">
<div class="line"><a id="l00696" name="l00696"></a><span class="lineno"><a class="line" href="namespaceshark.html#a8c16c27de8c5e84f4aa96b817a47834b">  696</a></span><span class="keyword">inline</span> std::size_t <a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(<a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;unsigned int&gt;</a> <span class="keyword">const</span>&amp; labels){</div>
<div class="line"><a id="l00697" name="l00697"></a><span class="lineno">  697</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(labels.data());</div>
<div class="line"><a id="l00698" name="l00698"></a><span class="lineno">  698</span>}</div>
</div>
<div class="line"><a id="l00699" name="l00699"></a><span class="lineno">  699</span><span class="comment"></span> </div>
<div class="line"><a id="l00700" name="l00700"></a><span class="lineno">  700</span><span class="comment">///\brief Returns the number of members of each class in the dataset.</span></div>
<div class="foldopen" id="foldopen00701" data-start="{" data-end="}">
<div class="line"><a id="l00701" name="l00701"></a><span class="lineno"><a class="line" href="namespaceshark.html#adc7cc86cef4519fa12ea88f07f0542f8">  701</a></span><span class="comment"></span><span class="keyword">inline</span> std::vector&lt;std::size_t&gt; <a class="code hl_function" href="group__shark__globals.html#ga89490b7ed6f9285ab91cae348c7437b8" title="Returns the number of members of each class in the dataset.">classSizes</a>(<a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;unsigned int&gt;</a> <span class="keyword">const</span>&amp; labels){</div>
<div class="line"><a id="l00702" name="l00702"></a><span class="lineno">  702</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga89490b7ed6f9285ab91cae348c7437b8" title="Returns the number of members of each class in the dataset.">classSizes</a>(labels.data());</div>
<div class="line"><a id="l00703" name="l00703"></a><span class="lineno">  703</span>}</div>
</div>
<div class="line"><a id="l00704" name="l00704"></a><span class="lineno">  704</span><span class="comment"></span> </div>
<div class="line"><a id="l00705" name="l00705"></a><span class="lineno">  705</span><span class="comment">///\brief  Return the dimnsionality of points of a weighted dataset</span></div>
<div class="line"><a id="l00706" name="l00706"></a><span class="lineno">  706</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> InputType&gt;</div>
<div class="foldopen" id="foldopen00707" data-start="{" data-end="}">
<div class="line"><a id="l00707" name="l00707"></a><span class="lineno"><a class="line" href="namespaceshark.html#a12497998181e61d460632d5bec46f5c5">  707</a></span>std::size_t <a class="code hl_function" href="group__shark__globals.html#ga6231b46b09731352a3cac40709a9625f" title="Return the dimensionality of a dataset.">dataDimension</a>(<a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00708" name="l00708"></a><span class="lineno">  708</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga6231b46b09731352a3cac40709a9625f" title="Return the dimensionality of a dataset.">dataDimension</a>(dataset.data());</div>
<div class="line"><a id="l00709" name="l00709"></a><span class="lineno">  709</span>}</div>
</div>
<div class="line"><a id="l00710" name="l00710"></a><span class="lineno">  710</span><span class="comment"></span> </div>
<div class="line"><a id="l00711" name="l00711"></a><span class="lineno">  711</span><span class="comment">///\brief  Return the input dimensionality of a weighted labeled dataset.</span></div>
<div class="line"><a id="l00712" name="l00712"></a><span class="lineno">  712</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00713" data-start="{" data-end="}">
<div class="line"><a id="l00713" name="l00713"></a><span class="lineno"><a class="line" href="namespaceshark.html#a1a4ae1c1461484d67c14d765c9db9501">  713</a></span>std::size_t <a class="code hl_function" href="group__shark__globals.html#gae537f0e90beb970397cd7bb9250984e2" title="Return the input dimensionality of a labeled dataset.">inputDimension</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType, LabelType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00714" name="l00714"></a><span class="lineno">  714</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga6231b46b09731352a3cac40709a9625f" title="Return the dimensionality of a dataset.">dataDimension</a>(dataset.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ad11b0613785e1c6f36f6dd5d32662ead" title="Access to the inputs as a separate container.">inputs</a>());</div>
<div class="line"><a id="l00715" name="l00715"></a><span class="lineno">  715</span>}</div>
</div>
<div class="line"><a id="l00716" name="l00716"></a><span class="lineno">  716</span><span class="comment"></span> </div>
<div class="line"><a id="l00717" name="l00717"></a><span class="lineno">  717</span><span class="comment">///\brief  Return the label/output dimensionality of a labeled dataset.</span></div>
<div class="line"><a id="l00718" name="l00718"></a><span class="lineno">  718</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00719" data-start="{" data-end="}">
<div class="line"><a id="l00719" name="l00719"></a><span class="lineno"><a class="line" href="namespaceshark.html#a1514586242fb20c13fa7d40e634efab7">  719</a></span>std::size_t <a class="code hl_function" href="group__shark__globals.html#ga3006553139477e356ee75cd85c190d7c" title="Return the label/output dimensionality of a labeled dataset.">labelDimension</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType, LabelType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00720" name="l00720"></a><span class="lineno">  720</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga6231b46b09731352a3cac40709a9625f" title="Return the dimensionality of a dataset.">dataDimension</a>(dataset.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>());</div>
<div class="line"><a id="l00721" name="l00721"></a><span class="lineno">  721</span>}<span class="comment"></span></div>
</div>
<div class="line"><a id="l00722" name="l00722"></a><span class="lineno">  722</span><span class="comment">///\brief Return the number of classes (highest label value +1) of a classification dataset with unsigned int label encoding</span></div>
<div class="line"><a id="l00723" name="l00723"></a><span class="lineno">  723</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> InputType&gt;</div>
<div class="foldopen" id="foldopen00724" data-start="{" data-end="}">
<div class="line"><a id="l00724" name="l00724"></a><span class="lineno"><a class="line" href="namespaceshark.html#ac00756ac00a20cb161c69cbb30bb0ee3">  724</a></span>std::size_t <a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType, unsigned int&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00725" name="l00725"></a><span class="lineno">  725</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(dataset.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>());</div>
<div class="line"><a id="l00726" name="l00726"></a><span class="lineno">  726</span>}</div>
</div>
<div class="line"><a id="l00727" name="l00727"></a><span class="lineno">  727</span><span class="comment"></span> </div>
<div class="line"><a id="l00728" name="l00728"></a><span class="lineno">  728</span><span class="comment">///\brief Returns the number of members of each class in the dataset.</span></div>
<div class="line"><a id="l00729" name="l00729"></a><span class="lineno">  729</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00730" data-start="{" data-end="}">
<div class="line"><a id="l00730" name="l00730"></a><span class="lineno"><a class="line" href="namespaceshark.html#a01fc9327a0b630c4f5458e7978cc363c">  730</a></span><span class="keyword">inline</span> std::vector&lt;std::size_t&gt; <a class="code hl_function" href="group__shark__globals.html#ga89490b7ed6f9285ab91cae348c7437b8" title="Returns the number of members of each class in the dataset.">classSizes</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType, LabelType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00731" name="l00731"></a><span class="lineno">  731</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#ga89490b7ed6f9285ab91cae348c7437b8" title="Returns the number of members of each class in the dataset.">classSizes</a>(dataset.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ae3ca78f96dd1c1881b04d3726213a136" title="Access to the labels as a separate container.">labels</a>());</div>
<div class="line"><a id="l00732" name="l00732"></a><span class="lineno">  732</span>}</div>
</div>
<div class="line"><a id="l00733" name="l00733"></a><span class="lineno">  733</span><span class="comment"></span> </div>
<div class="line"><a id="l00734" name="l00734"></a><span class="lineno">  734</span><span class="comment">///\brief Returns the total sum of weights.</span></div>
<div class="line"><a id="l00735" name="l00735"></a><span class="lineno">  735</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType&gt;</div>
<div class="foldopen" id="foldopen00736" data-start="{" data-end="}">
<div class="line"><a id="l00736" name="l00736"></a><span class="lineno"><a class="line" href="namespaceshark.html#ad53c908307c4f68be02eb87dad27a608">  736</a></span><span class="keywordtype">double</span> <a class="code hl_function" href="namespaceshark.html#ad53c908307c4f68be02eb87dad27a608" title="Returns the total sum of weights.">sumOfWeights</a>(<a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00737" name="l00737"></a><span class="lineno">  737</span>    <span class="keywordtype">double</span> weightSum = 0;</div>
<div class="line"><a id="l00738" name="l00738"></a><span class="lineno">  738</span>    <span class="keywordflow">for</span>(std::size_t i = 0; i != dataset.numberOfBatches(); ++i){</div>
<div class="line"><a id="l00739" name="l00739"></a><span class="lineno">  739</span>        weightSum += sum(dataset.batch(i).weight);</div>
<div class="line"><a id="l00740" name="l00740"></a><span class="lineno">  740</span>    }</div>
<div class="line"><a id="l00741" name="l00741"></a><span class="lineno">  741</span>    <span class="keywordflow">return</span> weightSum;</div>
<div class="line"><a id="l00742" name="l00742"></a><span class="lineno">  742</span>}<span class="comment"></span></div>
</div>
<div class="line"><a id="l00743" name="l00743"></a><span class="lineno">  743</span><span class="comment">///\brief Returns the total sum of weights.</span></div>
<div class="line"><a id="l00744" name="l00744"></a><span class="lineno">  744</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00745" data-start="{" data-end="}">
<div class="line"><a id="l00745" name="l00745"></a><span class="lineno"><a class="line" href="namespaceshark.html#a8f9d752ea6a5b99e4ec04515844760a6">  745</a></span><span class="keywordtype">double</span> <a class="code hl_function" href="namespaceshark.html#ad53c908307c4f68be02eb87dad27a608" title="Returns the total sum of weights.">sumOfWeights</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType,LabelType&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00746" name="l00746"></a><span class="lineno">  746</span>    <span class="keywordtype">double</span> weightSum = 0;</div>
<div class="line"><a id="l00747" name="l00747"></a><span class="lineno">  747</span>    <span class="keywordflow">for</span>(std::size_t i = 0; i != dataset.numberOfBatches(); ++i){</div>
<div class="line"><a id="l00748" name="l00748"></a><span class="lineno">  748</span>        weightSum += sum(dataset.batch(i).weight);</div>
<div class="line"><a id="l00749" name="l00749"></a><span class="lineno">  749</span>    }</div>
<div class="line"><a id="l00750" name="l00750"></a><span class="lineno">  750</span>    <span class="keywordflow">return</span> weightSum;</div>
<div class="line"><a id="l00751" name="l00751"></a><span class="lineno">  751</span>}</div>
</div>
<div class="line"><a id="l00752" name="l00752"></a><span class="lineno">  752</span><span class="comment"></span> </div>
<div class="line"><a id="l00753" name="l00753"></a><span class="lineno">  753</span><span class="comment">/// \brief Computes the cumulative weight of every class.</span></div>
<div class="line"><a id="l00754" name="l00754"></a><span class="lineno">  754</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType&gt;</div>
<div class="foldopen" id="foldopen00755" data-start="{" data-end="}">
<div class="line"><a id="l00755" name="l00755"></a><span class="lineno"><a class="line" href="namespaceshark.html#ac661a3b9018ce302c0af5c45450adb40">  755</a></span>RealVector <a class="code hl_function" href="namespaceshark.html#ac661a3b9018ce302c0af5c45450adb40" title="Computes the cumulative weight of every class.">classWeight</a>(<a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType,unsigned int&gt;</a> <span class="keyword">const</span>&amp; dataset){</div>
<div class="line"><a id="l00756" name="l00756"></a><span class="lineno">  756</span>    RealVector weights(<a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(dataset),0.0);</div>
<div class="line"><a id="l00757" name="l00757"></a><span class="lineno">  757</span>    <span class="keywordflow">for</span>(<span class="keyword">auto</span> <span class="keyword">const</span>&amp; elem: dataset.elements()){</div>
<div class="line"><a id="l00758" name="l00758"></a><span class="lineno">  758</span>        weights(elem.data.label) += elem.weight;</div>
<div class="line"><a id="l00759" name="l00759"></a><span class="lineno">  759</span>    }</div>
<div class="line"><a id="l00760" name="l00760"></a><span class="lineno">  760</span>    <span class="keywordflow">return</span> weights;</div>
<div class="line"><a id="l00761" name="l00761"></a><span class="lineno">  761</span>}</div>
</div>
<div class="line"><a id="l00762" name="l00762"></a><span class="lineno">  762</span> </div>
<div class="line"><a id="l00763" name="l00763"></a><span class="lineno">  763</span><span class="comment">//creation of weighted datasets</span></div>
<div class="line"><a id="l00764" name="l00764"></a><span class="lineno">  764</span><span class="comment"></span> </div>
<div class="line"><a id="l00765" name="l00765"></a><span class="lineno">  765</span><span class="comment">/// \brief creates a weighted unweighted data object from two ranges, representing data and weights</span></div>
<div class="line"><a id="l00766" name="l00766"></a><span class="lineno">  766</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputRange,<span class="keyword">class</span> LabelRange, <span class="keyword">class</span> WeightRange&gt;</div>
<div class="line"><a id="l00767" name="l00767"></a><span class="lineno">  767</span><span class="keyword">typename</span> boost::disable_if&lt;</div>
<div class="line"><a id="l00768" name="l00768"></a><span class="lineno">  768</span>    boost::is_arithmetic&lt;WeightRange&gt;,</div>
<div class="line"><a id="l00769" name="l00769"></a><span class="lineno">  769</span>    WeightedLabeledData&lt;</div>
<div class="line"><a id="l00770" name="l00770"></a><span class="lineno">  770</span>        <span class="keyword">typename</span> boost::range_value&lt;InputRange&gt;::type,</div>
<div class="line"><a id="l00771" name="l00771"></a><span class="lineno">  771</span>        <span class="keyword">typename</span> boost::range_value&lt;LabelRange&gt;::type</div>
<div class="line"><a id="l00772" name="l00772"></a><span class="lineno">  772</span>    &gt;</div>
<div class="foldopen" id="foldopen00773" data-start="{" data-end="}">
<div class="line"><a id="l00773" name="l00773"></a><span class="lineno"><a class="line" href="namespaceshark.html#aa0791f90b873248bed8c9f7be007cd2a">  773</a></span>&gt;::type <a class="code hl_function" href="group__shark__globals.html#ga409b50a287df842bd49e7434a8bbf69e" title="creates a labeled data object from two ranges, representing inputs and labels">createLabeledDataFromRange</a>(InputRange <span class="keyword">const</span>&amp; inputs, LabelRange <span class="keyword">const</span>&amp; labels, WeightRange <span class="keyword">const</span>&amp; weights, std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = 0){</div>
<div class="line"><a id="l00774" name="l00774"></a><span class="lineno">  774</span> </div>
<div class="line"><a id="l00775" name="l00775"></a><span class="lineno">  775</span>    <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(inputs) == <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(labels),</div>
<div class="line"><a id="l00776" name="l00776"></a><span class="lineno">  776</span>    <span class="stringliteral">&quot;number of inputs and number of labels must agree&quot;</span>);</div>
<div class="line"><a id="l00777" name="l00777"></a><span class="lineno">  777</span>    <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(inputs) == <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(weights),</div>
<div class="line"><a id="l00778" name="l00778"></a><span class="lineno">  778</span>    <span class="stringliteral">&quot;number of data points and number of weights must agree&quot;</span>);</div>
<div class="line"><a id="l00779" name="l00779"></a><span class="lineno">  779</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> boost::range_value&lt;InputRange&gt;::type <a class="code hl_typedef" href="_multi_task_svm_8cpp.html#a0dea9a3a85d327080d9b617903508925">InputType</a>;</div>
<div class="line"><a id="l00780" name="l00780"></a><span class="lineno">  780</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> boost::range_value&lt;LabelRange&gt;::type LabelType;</div>
<div class="line"><a id="l00781" name="l00781"></a><span class="lineno">  781</span> </div>
<div class="line"><a id="l00782" name="l00782"></a><span class="lineno">  782</span>    <span class="keywordflow">if</span> (<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> == 0)</div>
<div class="line"><a id="l00783" name="l00783"></a><span class="lineno">  783</span>        <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputRange,LabelRange&gt;::DefaultBatchSize</a>;</div>
<div class="line"><a id="l00784" name="l00784"></a><span class="lineno">  784</span> </div>
<div class="line"><a id="l00785" name="l00785"></a><span class="lineno">  785</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType,LabelType&gt;</a>(</div>
<div class="line"><a id="l00786" name="l00786"></a><span class="lineno">  786</span>        <a class="code hl_function" href="group__shark__globals.html#ga409b50a287df842bd49e7434a8bbf69e" title="creates a labeled data object from two ranges, representing inputs and labels">createLabeledDataFromRange</a>(inputs,labels,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>),</div>
<div class="line"><a id="l00787" name="l00787"></a><span class="lineno">  787</span>        <a class="code hl_function" href="group__shark__globals.html#ga1a1a4f4249f709e6169a601a9a857fa8" title="creates a data object from a range of elements">createDataFromRange</a>(weights,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>)</div>
<div class="line"><a id="l00788" name="l00788"></a><span class="lineno">  788</span>    );</div>
<div class="line"><a id="l00789" name="l00789"></a><span class="lineno">  789</span>}</div>
</div>
<div class="line"><a id="l00790" name="l00790"></a><span class="lineno">  790</span><span class="comment"></span> </div>
<div class="line"><a id="l00791" name="l00791"></a><span class="lineno">  791</span><span class="comment">/// \brief Creates a bootstrap partition of a labeled dataset and returns it using weighting.</span></div>
<div class="line"><a id="l00792" name="l00792"></a><span class="lineno">  792</span><span class="comment">///</span></div>
<div class="line"><a id="l00793" name="l00793"></a><span class="lineno">  793</span><span class="comment">/// Bootstrapping resamples the dataset by drawing a set of points with</span></div>
<div class="line"><a id="l00794" name="l00794"></a><span class="lineno">  794</span><span class="comment">/// replacement. Thus the sampled set will contain some points multiple times</span></div>
<div class="line"><a id="l00795" name="l00795"></a><span class="lineno">  795</span><span class="comment">/// and some points not at all. Bootstrapping is usefull to obtain unbiased</span></div>
<div class="line"><a id="l00796" name="l00796"></a><span class="lineno">  796</span><span class="comment">/// measurements of the mean and variance of an estimator.</span></div>
<div class="line"><a id="l00797" name="l00797"></a><span class="lineno">  797</span><span class="comment">///</span></div>
<div class="line"><a id="l00798" name="l00798"></a><span class="lineno">  798</span><span class="comment">/// Optionally the size of the bootstrap (that is, the number of sampled points)</span></div>
<div class="line"><a id="l00799" name="l00799"></a><span class="lineno">  799</span><span class="comment">/// can be set. By default it is 0, which indicates that it is the same size as the original dataset.</span></div>
<div class="line"><a id="l00800" name="l00800"></a><span class="lineno">  800</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00801" data-start="{" data-end="}">
<div class="line"><a id="l00801" name="l00801"></a><span class="lineno"><a class="line" href="namespaceshark.html#a23d76a81bf28d05f9357d236a63a17c8">  801</a></span><a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt; InputType, LabelType&gt;</a> <a class="code hl_function" href="namespaceshark.html#a23d76a81bf28d05f9357d236a63a17c8" title="Creates a bootstrap partition of a labeled dataset and returns it using weighting.">bootstrap</a>(</div>
<div class="line"><a id="l00802" name="l00802"></a><span class="lineno">  802</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType,LabelType&gt;</a> <span class="keyword">const</span>&amp; dataset,</div>
<div class="line"><a id="l00803" name="l00803"></a><span class="lineno">  803</span>    std::size_t bootStrapSize = 0</div>
<div class="line"><a id="l00804" name="l00804"></a><span class="lineno">  804</span>){</div>
<div class="line"><a id="l00805" name="l00805"></a><span class="lineno">  805</span>    <span class="keywordflow">if</span>(bootStrapSize == 0)</div>
<div class="line"><a id="l00806" name="l00806"></a><span class="lineno">  806</span>        bootStrapSize = dataset.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00807" name="l00807"></a><span class="lineno">  807</span>    </div>
<div class="line"><a id="l00808" name="l00808"></a><span class="lineno">  808</span>    <a class="code hl_class" href="classshark_1_1_weighted_labeled_data.html" title="Weighted data set for supervised learning.">WeightedLabeledData&lt;InputType,LabelType&gt;</a> bootstrapSet(dataset,0.0);</div>
<div class="line"><a id="l00809" name="l00809"></a><span class="lineno">  809</span> </div>
<div class="line"><a id="l00810" name="l00810"></a><span class="lineno">  810</span>    <span class="keywordflow">for</span>(std::size_t i = 0; i != bootStrapSize; ++i){</div>
<div class="line"><a id="l00811" name="l00811"></a><span class="lineno">  811</span>        std::size_t index = <a class="code hl_function" href="namespaceshark_1_1random.html#aa64d4174eaf7111b03e0504eaa56b666" title="Draws a discrete number in {low,low+1,...,high} by drawing random numbers from rng.">random::discrete</a>(<a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>, std::size_t(0),bootStrapSize-1);</div>
<div class="line"><a id="l00812" name="l00812"></a><span class="lineno">  812</span>        bootstrapSet.element(index).weight += 1.0;</div>
<div class="line"><a id="l00813" name="l00813"></a><span class="lineno">  813</span>    }</div>
<div class="line"><a id="l00814" name="l00814"></a><span class="lineno">  814</span>    bootstrapSet.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#a4b369aa6cfa440ecb7f5a150e645a2a9" title="Returns the Shape of the inputs.">inputShape</a>() = dataset.<a class="code hl_function" href="group__shark__globals.html#ga134d41e34c69c494346367a570bf4ff8" title="Returns the Shape of the inputs.">inputShape</a>();</div>
<div class="line"><a id="l00815" name="l00815"></a><span class="lineno">  815</span>    bootstrapSet.<a class="code hl_function" href="classshark_1_1_weighted_labeled_data.html#ab551802a4a3d30b09984ee7c92ca64b5" title="Returns the Shape of the labels.">labelShape</a>() = dataset.<a class="code hl_function" href="group__shark__globals.html#ga7f3308a970a6f4fe96aebf23755a6430" title="Returns the Shape of the labels.">labelShape</a>();</div>
<div class="line"><a id="l00816" name="l00816"></a><span class="lineno">  816</span>    <span class="keywordflow">return</span> bootstrapSet;</div>
<div class="line"><a id="l00817" name="l00817"></a><span class="lineno">  817</span>}</div>
</div>
<div class="line"><a id="l00818" name="l00818"></a><span class="lineno">  818</span><span class="comment"></span> </div>
<div class="line"><a id="l00819" name="l00819"></a><span class="lineno">  819</span><span class="comment">/// \brief Creates a bootstrap partition of an unlabeled dataset and returns it using weighting.</span></div>
<div class="line"><a id="l00820" name="l00820"></a><span class="lineno">  820</span><span class="comment">///</span></div>
<div class="line"><a id="l00821" name="l00821"></a><span class="lineno">  821</span><span class="comment">/// Bootstrapping resamples the dataset by drawing a set of points with</span></div>
<div class="line"><a id="l00822" name="l00822"></a><span class="lineno">  822</span><span class="comment">/// replacement. Thus the sampled set will contain some points multiple times</span></div>
<div class="line"><a id="l00823" name="l00823"></a><span class="lineno">  823</span><span class="comment">/// and some points not at all. Bootstrapping is usefull to obtain unbiased</span></div>
<div class="line"><a id="l00824" name="l00824"></a><span class="lineno">  824</span><span class="comment">/// measurements of the mean and variance of an estimator.</span></div>
<div class="line"><a id="l00825" name="l00825"></a><span class="lineno">  825</span><span class="comment">///</span></div>
<div class="line"><a id="l00826" name="l00826"></a><span class="lineno">  826</span><span class="comment">/// Optionally the size of the bootstrap (that is, the number of sampled points)</span></div>
<div class="line"><a id="l00827" name="l00827"></a><span class="lineno">  827</span><span class="comment">/// can be set. By default it is 0, which indicates that it is the same size as the original dataset.</span></div>
<div class="line"><a id="l00828" name="l00828"></a><span class="lineno">  828</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType&gt;</div>
<div class="foldopen" id="foldopen00829" data-start="{" data-end="}">
<div class="line"><a id="l00829" name="l00829"></a><span class="lineno"><a class="line" href="namespaceshark.html#a78ea17b764fda3618970ff23a975ea3e">  829</a></span><a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a> <a class="code hl_function" href="namespaceshark.html#a23d76a81bf28d05f9357d236a63a17c8" title="Creates a bootstrap partition of a labeled dataset and returns it using weighting.">bootstrap</a>(</div>
<div class="line"><a id="l00830" name="l00830"></a><span class="lineno">  830</span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;InputType&gt;</a> <span class="keyword">const</span>&amp; dataset,</div>
<div class="line"><a id="l00831" name="l00831"></a><span class="lineno">  831</span>    std::size_t bootStrapSize = 0</div>
<div class="line"><a id="l00832" name="l00832"></a><span class="lineno">  832</span>){</div>
<div class="line"><a id="l00833" name="l00833"></a><span class="lineno">  833</span>    <span class="keywordflow">if</span>(bootStrapSize == 0)</div>
<div class="line"><a id="l00834" name="l00834"></a><span class="lineno">  834</span>        bootStrapSize = dataset.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00835" name="l00835"></a><span class="lineno">  835</span>    </div>
<div class="line"><a id="l00836" name="l00836"></a><span class="lineno">  836</span>    <a class="code hl_class" href="classshark_1_1_weighted_unlabeled_data.html" title="Weighted data set for unsupervised learning.">WeightedUnlabeledData&lt;InputType&gt;</a> bootstrapSet(dataset,0.0);</div>
<div class="line"><a id="l00837" name="l00837"></a><span class="lineno">  837</span> </div>
<div class="line"><a id="l00838" name="l00838"></a><span class="lineno">  838</span>    <span class="keywordflow">for</span>(std::size_t i = 0; i != bootStrapSize; ++i){</div>
<div class="line"><a id="l00839" name="l00839"></a><span class="lineno">  839</span>        std::size_t index = <a class="code hl_function" href="namespaceshark_1_1random.html#aa64d4174eaf7111b03e0504eaa56b666" title="Draws a discrete number in {low,low+1,...,high} by drawing random numbers from rng.">random::discrete</a>(<a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>, std::size_t(0),bootStrapSize-1);</div>
<div class="line"><a id="l00840" name="l00840"></a><span class="lineno">  840</span>        bootstrapSet.element(index).weight += 1.0;</div>
<div class="line"><a id="l00841" name="l00841"></a><span class="lineno">  841</span>    }</div>
<div class="line"><a id="l00842" name="l00842"></a><span class="lineno">  842</span>    bootstrapSet.<a class="code hl_function" href="classshark_1_1_weighted_unlabeled_data.html#a928b2414d9a32987c3341743dc0716e4" title="Returns the Shape of the data.">shape</a>() = dataset.<a class="code hl_function" href="group__shark__globals.html#gabdfa24d4e424c86cf39851c143b2dd37" title="Returns the shape of the elements in the dataset.">shape</a>();</div>
<div class="line"><a id="l00843" name="l00843"></a><span class="lineno">  843</span>    <span class="keywordflow">return</span> bootstrapSet;</div>
<div class="line"><a id="l00844" name="l00844"></a><span class="lineno">  844</span>}</div>
</div>
<div class="line"><a id="l00845" name="l00845"></a><span class="lineno">  845</span> </div>
<div class="line"><a id="l00846" name="l00846"></a><span class="lineno">  846</span>}</div>
<div class="line"><a id="l00847" name="l00847"></a><span class="lineno">  847</span> </div>
<div class="line"><a id="l00848" name="l00848"></a><span class="lineno">  848</span><span class="preprocessor">#endif</span></div>
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